Business intelligence (BI) combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions. In practice, you know you’ve got modern business intelligence when you have a comprehensive view of your organization’s data and use that data to drive change, eliminate inefficiencies, and quickly adapt to market or supply changes.

It’s important to note that this is a very modern definition of BI—and BI has had a strangled history as a buzzword. Traditional Business Intelligence, capital letters and all, originally emerged in the 1960s as a system of sharing information across organizations.

It further developed in the 1980s alongside computer models for decision-making and turning data into insights before becoming specific offering from BI teams with IT-reliant service solutions. Modern BI solutions prioritize flexible self-service analysis, governed data on trusted platforms, empowered business users, and speed to insight.

• What is Business Intelligence in Simple Terms?
• What is Business Intelligence With Examples?
• What is Business Intelligence Skills?
• What is The Role of Business Intelligence?
• Business Intelligence System
• Business Intelligence Analyst
• Business Intelligence Salary
• Business Intelligence Course
• Business Intelligence vs Business Analytics
• Business Intelligence in Information Technology
• What Are The Five Tasks of Business Intelligence?
• What Problems Can Business Intelligence Solve?
• What Companies Use Business Intelligence?
• How do You do Business Intelligence?
• What Skills Are Needed For Business Intelligence?
• Can Python be Used For Business Intelligence?
• Is Business Intelligence a Good Career?
• Is Excel a Business Intelligence Tool?
• What is The Most Popular Business Intelligence Software?
• What Are The Main Components of Business Intelligence?
• What Are Examples of Business Intelligence Tools?
• How Can Business Intelligence Help an Organization?
• How Walmart Uses Business Intelligence?
• How Does Netflix Use Business Intelligence?
• What is Business Intelligence Tools?
• Importance of Business Intelligence
• Benefits of Business Intelligence
• Sources of Business Intelligence
• Use of Business Intelligence
• Is There Coding in Business Intelligence?
• Who Can Become Business Intelligence Analyst?
• What Are The Types of Business Intelligence?
• What Are The Characteristics of Business Intelligence?
• Which Language is Used For Business Intelligence?
• How do I Start a Business Intelligence Career?

What is Business Intelligence in Simple Terms?

Business intelligence is the process by which enterprises use strategies and technologies for analyzing current and historical data, with the objective of improving strategic decision-making and providing a competitive advantage.

It systems combine data gathering, data storage, and knowledge management with data analysis to evaluate and transform complex data into meaningful, actionable information, which can be used to support more effective strategic, tactical, and operational insights and decision-making.

Read Also: What Can You do With a Business Degree?

Business intelligence environments consist of a variety of technologies, applications, processes, strategies, products, and technical architectures used to enable the collection, analysis, presentation, and dissemination of internal and external business information.

What is Business Intelligence With Examples?

Reporting is a central facet of business intelligence and the dashboard is perhaps the archetypical BI tool. Dashboards are hosted software applications that automatically pull together available data into charts and graphs that give a sense of the immediate state of the company.

Although business intelligence does not tell business users what to do or what will happen if they take a certain course, neither is BI solely about generating reports. Rather, BI offers a way for people to examine data to understand trends and derive insights by streamlining the effort needed to search for, merge and query the data necessary to make sound business decisions.

For example, a company that wants to better manage its supply chain needs BI capabilities to determine where delays are happening and where variabilities exist within the shipping process, says Chris Hagans, vice president of operations for WCI Consulting, a consultancy focused on BI. That company could also use its BI capabilities to discover which products are most commonly delayed or which modes of transportation are most often involved in delays.

The potential use cases for BI extend beyond the typical business performance metrics of improved sales and reduced costs, says Cindi Howson, research vice president at Gartner, an IT research and advisory firm.

She points to the Columbus, Ohio, school system and its success using BI tools to examine numerous data points — from attendance rates to student performance — to improve student learning and high school graduate rates.

BI vendors Tableau and G2 also offer concrete examples of how organizations might put business intelligence tools to use:

• A co-op organization could use BI to keep track of member acquisition and retention.
• BI tools could automatically generate sales and delivery reports from CRM data.
• A sales team could use BI to create a dashboard showing where each rep’s prospects are on the sales pipeline.

What is Business Intelligence Skills?

There are many skills that should be in the arsenal of a BI Analyst. Some of these are given below:

1. Data preparation

Data preparation is a very important part of Business Intelligence. To obtain any insights from the data, first, the data needs to be collected, cleaned, and organized in a uniform manner.

There are many data preparation tools that can collect data from various sources and then prepare this data with the same dimensions and measurements. And as a BI Analyst, you should be familiar with at least some of these data preparation tools like Tableau Prep, Improvado. Alteryx, etc.

2. Data mining

Data mining is the process of finding patterns in the data that were previously not visible. This converts the raw data into useful information that can be used for decision-making.

The knowledge of data mining requires an understanding of various technologies like machine learning, databases, statistical analysis, computer science algorithms, etc. Some of the tools that are very helpful in data mining include the Rapid Miner, Oracle data mining, Konstanz Information Miner, etc.

3. Statistical analysis

Knowledge of statistics is a big part of becoming a Business Intelligence Analyst. You should have knowledge of various statistical components like mean, median, range, variance, etc. can be used to get a more detailed view of the data.

And these are just the basics! Other advanced statistical topics like combinatorics, set theory, probability, discrete and continuous and bivariate distributions, random variables, etc. are also important. There are many analytical tools that can help businesses to understand their metrics better in order to create a sound BI strategy. These include SAS, Hadoop, Spark, Hive, Pig, etc.

4. Descriptive analysis

Description analysis involves researching the data to understand if there are any missing values, outliers, abnormal or skewed distributions, etc. In essence, it is a part of understanding and getting to know the data before presenting the data to decision-makers in a clean form.

There are many tools that can be used for descriptive analytics such as the statistical methods described above or data visualization charts that are used to study the data such as histograms, bar charts, box and whisker plots, etc.

5. Data visualization

As a BI analyst, a critical part of your job is not just to obtain the patterns in the data but to visualize the data in such a manner that these patterns are clearly visible. So data visualization skills are a big part of becoming a Business Intelligence Analyst.

You should have knowledge about various charts that can be used to visualize the data such as Area Charts, Bar Charts, Heat Maps, TreeMaps, Scatter Plots, Gantt Charts, etc. All these charts allow decision-makers to understand the data in more depth by visualizing it and understanding the slowly changing trends or the places where critical changes suddenly occur.

6. Business Knowledge

As a Business Intelligence Analyst, you should have sound business knowledge as well. You should be well acquainted with the business model of the company you are working for and understand how to leverage the data in order to obtain the maximum profit for the business based on the key performance indicators. You should understand both the short term and long term business goals of the company so that you can help in charting the future path with the help of data.

7. Data Reporting

Data Report skills or Communication skills are soft skills that are absolutely essential to your job as a business intelligence analyst. You should have the speaking skills to report the insights obtained from the data to higher-ups in the business such as the stakeholders and board members so that they can make the necessary decisions for the business.

Also, it is important to remember that most of the decision-makers might be from a technical background so it’s important to use layman language to explain technical concepts so that they are easily understandable.

What is The Role of Business Intelligence?

Companies adopting business intelligence solutions can turn business data into insights and take plausible action. These insights can help companies make strategic business decisions that increase productivity, improve revenues, and enhance growth.

There are many reasons why companies choose business intelligence solutions. If you’re contemplating BI software for your business, you may be wondering if it’s worth the time, effort, and expense to add it to your existing software suite.

BI-Tools was curious about whether BI software lived up to its hype and whether companies felt they got the maximum benefit from it. The results may help solidify your decision whether or not to add BI to your software suite.

• Better planning and analysis: Companies felt that BI systems helped them the most with faster reporting, planning, and analysis. 64% of responding companies ranked their ability to report, plan and analyze data as “good” after implementing a business intelligence suite.
• Increased accuracy: Among the companies surveyed, 56% felt that business intelligence data increased the accuracy of their business analysis and planning.
• Helped considerably with sales forecasting: Among the many tasks that companies felt that business intelligence data helped with, 57% ranked sales forecasting and planning as the area receiving the most benefit from BI data. Other areas where they felt that BI date provided assistance was in customer behavior analysis (40%) and a unified view of customers (32%).
• Improved pricing and offers: Pricing and offer optimization benefited somewhat from the implementation of a BI system. 27% of respondents felt that the additional data derived from their BI system helped them improve their pricing structure to become more competitive, as well as improve the attractiveness of their offers.

Business Intelligence System

Business Intelligence systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data. Software elements support reporting, interactive “slice-and-dice” pivot-table analyses, visualization, and statistical data mining.

Applications tackle sales, production, financial, and many other sources of business data for purposes that include business performance management. Information is often gathered about other companies in the same industry which is known as benchmarking.

Business Intelligence Analyst

Business intelligence (BI) analysts transform data into insights that drive business value. Through use of data analytics, data visualization and data modeling techniques and technologies, BI analysts can identify trends that can help other departments, managers and executives make business decisions to modernize and improve processes in the organization.

The BI analyst role is becoming increasingly important as organizations move to capitalize on the volumes of data they collect. BI analysts typically discover areas of revenue loss and identify where improvements can be made to save the company money or increase profits.

This is done by mining complex data using BI software and tools, comparing data to competitors and industry trends and creating visualizations that communicate findings to others in the organization.

BI analysts typically handle analysis and data modeling design using data collected in a centralized data warehouse or multiple databases throughout the organization. It’s a role that combines hard skills like programming, data modeling and statistics with soft skills like communication, analytical thinking and problem-solving. Candidates need a well-rounded background to balance the line between IT and the business.

You’ll need at least a bachelor’s degree in computer science, business, mathematics, economics, statistics, management, accounting or in a related field. If you have a degree in an unrelated field but have completed courses in these subjects, that can suffice for an entry-level role in some organizations. Other senior positions may require an MBA, but there are plenty of BI jobs that look only for an undergraduate degree.

To become a successful BI analyst, you’ll need a mix of technical, soft and analytical skills. The job requires you to mine data using complex tools and software and then analyze that data to find trends.

Once you spot data trends, you’ll need to effectively communicate your findings to others in the organization. You’ll also be responsible for suggesting possible solutions to fix issues that you find — especially if they’re tied to revenue loss.

Popular BI analyst skills include: 

• Data warehouse
• Data modeling
• Data mining
• Business intelligence
• Tableau and data visualization
• Hadoop, SQL, Python and C#
• Data analysis
• Business analysis
• Database management and reporting
• Business administration
• Microsoft Office and Excel
• Critical-thinking and problem-solving
• Communication skills

Business Intelligence Salary

According to data from PayScale, the average salary for a BI analyst is $66,645 per year, with a reported salary range of $48,701 to $93,243.

Salary data on similar positions includes:

Job title	Salary range	Average salary
Business intelligence director	$93,000-$163,000	$129,023
Director of analytics	$83,000-$171,000	$126,621
Senior manager business analytics	$87,000-$158,000	$120,762
Business intelligence manager	$70,000-$134,000	$100,947
Senior business intelligence analyst	$67,000-$117,000	$87,760
Business intelligence consultant	$55,000-$117,000	$84,348

PayScale also identifies cities where BI analysts earn salaries that are higher than the national average. These include San Francisco, CA (24%); Washington, DC (18%); Houston, TX (8%); Seattle, WA (7%); Boston, MA (7%); New York, NY (6%); Phoenix, AZ (4%); and Austin, TX (3%).

Business Intelligence Course

We’ve compiled this list of the best business intelligence courses and online training to consider if you’re looking to grow your data analytics skills for work or play. This is not an exhaustive list, but one that features the best business intelligence courses and training from trusted online platforms.

Business Intelligence Concepts, Tools, and Applications

Platform: Coursera

Description: This is the fourth course in the Data Warehouse for Business Intelligence specialization. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer.

You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy’s Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards.

Data Warehousing and BI Certification Training

Platform: Edureka

Description: Become an expert in data warehousing and business intelligence techniques covering concepts like DW architecture, data modeling, ERwin, ETL fundamentals, business reporting, and data visualisation. Key topics include top-down vs. bottom-up data warehouse design and classification of different BI tools and various ways to use them.

BI Reporting Tools Training

Platform: Intellipaat

Description: Intellipaat’s BI Reporting certification master’s program lets you gain proficiency in the top BI reporting tools. This training includes the BI reporting tools like QlikView, Spotfire, Tableau, Cognos, Cognos Insight, Pentaho, Jaspersoft, MicroStrategy, Hyperion, and SSRS. You will work on projects in data visualization, deploy dashboards, analytics, reports for deriving business insights, and more.

Business Intelligence for Consultants

Platform: LinkedIn Learning

Description: This course explains what business intelligence is, why it’s important, and how consultants can tap into business intelligence when delivering outcomes for clients. Instructor Joshua Rischin has been a consultant to over 40 organizations.

Here he shares techniques and examples from his career with you. Learn how to profile the client’s business, gather high-quality and relevant data, and present your insights and recommendations to clients with detailed visualizations and reports.

Cloud Business Intelligence: The Big Picture

Platform: Pluralsight

Description: This course covers the current state of Business Intelligence in the cloud, as well as goes into functional examples using Google Big Query and Tableau Online. This is a beginner course, but it is assumed you are familiar with the basics of databases and business intelligence concepts.

Tips to Win Business Intelligence (BI) Career Opportunities

Platform: Skillshare

Description: This course helps newcomers, recent graduates, or anyone interested in finding a BI job in data warehousing and analytics, with a focus on the SAP skillset. Additionally, the guidelines can also be applied to any BI job regardless of the specific tool or application.

Learn from a Business Intelligence IT professional with 12 years of experience in many different areas and sectors, someone who has been responsible for hiring many candidates at different levels with different responsibilities.

The Bussiness Intelligence Analyst Course 2020

Platform: Udemy

Description: Make sense of terms like business intelligence, traditional and big data, traditional statistical methods, machine learning, predictive analytics, supervised learning, unsupervised learning, reinforcement learning, and many more.

Understand statistical testing and build a solid foundation. Modern software packages and programming languages are automating most of these activities. This course is for beginners to programming and data science.

Business Intelligence vs Business Analytics

The distinctions between BI, data analytics, and business analytics are subtle, and to make things more confusing, the terms are often used interchangeably.

Business analytics (BA) refers to the practice of using your company’s data to anticipate trends and outcomes. BA includes data mining, statistical analysis, and predictive modeling that help make more informed decisions.

Data analytics is the technical process of mining data, cleaning data, transforming data, and building the systems to manage data. Data analytics takes large quantities of data to find trends and solve problems. Data analytics is used across disciplines—from government to science. It’s not just confined to business applications.

The major difference between business intelligence and business analytics is the questions they answer.

Business intelligence focuses on descriptive analytics
BI prioritizes descriptive analytics, which provides a summary of historical and present data to show what has happened or what is currently happening. BI answers the questions “what” and “how” so you can replicate what works and change what does not.

Business analytics focuses on predictive analytics
BA, however, prioritizes predictive analytics, which uses data mining, modeling and machine learning to determine the likelihood of future outcomes. BA answers the question “why” so it can make more educated predictions about what will happen. With BA, you can anticipate developments and make the changes necessary to succeed.

Applying BI and BA in the real world
Let’s illustrate these differences with real-world applications of BI and BA. In this example, you sell homemade jewelry through an online store. Business intelligence provides helpful reports of the past and current state of your business. BI tells you that sales of your blue feather earrings have spiked in Utah the past three weeks. As a result, you decide to make more blue feather earrings to keep up with demand.

Business analytics asks, “Why did sales of blue feather earrings spike in Utah?” By mining your website data, you learn that a majority of traffic has come from a post by a Salt Lake City fashion blogger who wore your earrings.

This insight helps you decide to send complimentary earrings to a few other prominent fashion bloggers throughout the US. You use the previous sales information to anticipate how many earrings you will need to make and how much supplies you will need to order to keep up with demand if the bloggers were to post about the earrings.

Business Intelligence in Information Technology

Organizations maintain and analyze large volumes of data. IT departments are quickly becoming overloaded with reporting requests, training, and user support. Business intelligence (BI) initiatives are the key to reducing the ad hoc reporting workload of analysts, reducing the helpdesk support time, and increasing the data security of the organization.

Business intelligence is the process of storing, accessing, analyzing, and visualizing data to make better business decisions. BI and information technology are closely intertwined. Both initiatives deal with information management and data. Self-service business intelligence enables IT to be more proactive and focus on governance, instead of reacting to each reporting request and support call.

BI platforms by design are a one-stop-shop for data. Is your team continually responding to reporting requests? Does your organization juggle multiple technology solutions for data analysis and data storage? If your answer is yes, here’s how modern BI solutions can help:

1. Integrate with your existing data architecture

Modern BI platforms are designed to support current IT infrastructure and data storage. If your organization has already invested in a data warehouse and data marts, the best BI solution for you will integrate with that system without middle-tier platforms.

2. Security

BI platforms take data security seriously. Only the users who need data will be able to access it. IT should be able to set up data permissions easily, and dashboards and reporting functions should only pull in data that the user has permissions to see.

3. Data Storage

BI can access multiple data sources from within a data warehouse, including databases with financial data, operational data, and CRM data seamlessly. With traditional data storage solutions, accessing data from multiple sources can be slow and difficult. The University of Notre Dame recognized their data lived in silos by department; modern BI enabled them to access the data and create reports quickly.

4. Scalability

Enterprise BI platforms like Tableau are designed to scale from one-person users to entire corporations. We have examples of organizations scaling up their BI initiatives to thousands of users. You should have the ability to use your BI platform with your current operating system, have mobile capabilities, and have both remote and on-premises access.

Business intelligence isn’t just another IT project. It is a process and program intertwined with business operations through a platform. Once deployed, ownership belongs to business analysts or a special BI team. IT departments can focus on data governance and oversight of these platforms, and end-users can complete their own analyses. Success from BI platforms means success for all data teams, including IT.

Business intelligence in the IT industry empowers departments to focus on their own performance. Leaders can customize dashboards to track key performance indicators, such as helpdesk ticket closure rates. BI can help IT create their own plan for the future of the department by focusing on return on investment in technology solutions.

What Are The Five Tasks of Business Intelligence?

We will learn about 5 tasks, which can be automated in Business Intelligence and Analytics:

1. Auto-discover insights

Business intelligence tools should understand the query to be asked and quickly find valuable insights without the need for humans. Business intelligence can do this by automating the logic and interpretation of discovery.

With the help of artificial intelligence in BI and the powerful functions of PCs, business intelligence programming can make full use of all the prospects in the data, not only what customers think or have the opportunity to do.

2. Automate the ranking of insights

At the point when you automate discovery, a lot more insights are uncovered. Google’s PageRank algorithm has the most suitable website pages, and relatively speaking, automated business intelligence programs can highlight the most important dynamic insights. In addition, BI with artificial intelligence can perceive the connexions between insights, making it easier for customers to analyse different insights at the same time.

3. Embedded Insights

With Business Intelligence and AI for automation, it is easy to connect insights with the applications used by business customers. At the point when insights are introduced at the purpose of-use, clients may never have to use a business intelligence tool straightforwardly.

Through automation, business intelligence programming will become the driving force for another programming. Daily business measures become more efficient and productivity continues to increase. The administrator reduces the investment in business

intelligence tasks, and devotes more energy to solving the company’s decisions.

4. Extract Bias

When using business intelligence and AI, data will drive automation, and customers will no longer need to work manually to derive insights, reducing the margins of human error. Client errors can be caused by unilateral decisions, simplified suspicions, flawed observations, outdated opinions, negative behavior patterns, and sincere beliefs.

The automation of artificial intelligence eliminates the aforementioned factors, thereby limiting the risk of losing data or being affected by bias in the results

5. Universal Accessibility

For what reason can’t finding insight in data analysis be as straightforward as utilizing Google search to discover a page on the web? With artificial intelligence, it very well maybe. When business intelligence is automated, every business customer can click a button and immediately get expert help from the BI platform that supports it as a decision support system.

Subsequently, business customers will not need any preparation or data science skills to solve smart decisions.

What Problems Can Business Intelligence Solve?

By incorporating a Business Intelligence solution into your daily business operations, you can solve a wide variety of problems, from high costs to low customer satisfaction. Every small, mid-sized, and large business can benefit from BI, especially now, as Business Intelligence platforms are not only more affordable than they were in the past but also easier to implement.

1. Poor Performance Management

You have a great product or service, your visionary approach is making a difference, but how is your business doing now or over a two-year period?

When you have access to meaningful analysis and reporting, you can make well-informed and insightful, long-term strategic and tactical decisions quickly and efficiently. With Business Intelligence, you gain insight into understanding and analyzing your business’ performance and opportunities on a deeper level.

You can track and analyze KPIs against key business goals to gain a better understanding of how your business is performing today – rather than at a time when it’s too late to impact performance.

Furthermore, it will be easier to take proactive measures to improve performance and meet profit expectations.

2. Slow Market Response

A.K.A. losing money right now. One of the biggest strengths of having a BI solution in your company is having the ability to look into what the market is purchasing now. You can view reports on a daily basis instead of waiting until the end of the month or quarter, enabling you to respond quickly to unpredictable situations and market demands.

For example, you can see how many pieces of certain products were sold and in which location, which can help your sales personnel cross-sell and upsell goods at the most appropriate client touch points. This kind of data can be utilized to develop an advantage over the competition and increase profit.

3. Losing Customers

With Business Intelligence, you can gain valuable insight into your customer behavior by certain metrics and analyses. You can create detailed guest profiles that include interests, preferences, history, and more. Armed with this information, you can anticipate clients’ needs and offer more personalized services or create a more memorable customer experience and build long-term relationships.

4. Chaos in Day-to-Day Operations

From financial data in spreadsheets with special macros to sales and performance metrics on different reports, dealing with all kinds of data in everyday operations can create chaos.

Integrating Business Intelligence into your day-to-day operations can improve alignment with a single source for accurate financial and operational information and simplify collaboration and sharing.

Having a single, central location allows all teams to monitor key performance indicators (KPIs), access reports, analyze your data, and share documents. The data is gathered electronically and delivered in an easy-to-understand format, allowing even the most non-technical users to determine the factors that drive day-to-day activity.

5. Wasting Time on Compiling Multiple Systems Instead of Analyzing Data

Many organizations throw away valuable time and energy looking for pertinent information from within their different data sources. Much time is invested converting, merging, and reporting data, discussing whether it is accurate, not to mention that desktop spreadsheets do not enable real-time data sharing and updating.

With a BI system in place, all of the data required comes from one source and can be accessed from one dashboard and converted into a report. This saves both time and energy while making the process much more efficient.

Extracting data from these multiple sources and bringing it together into a centralized data warehouse can make it much easier to gain quick and reliable insights.

6. Reliance on Tech Teams to Develop Custom Reports

Many traditional data tools are so complicated that only a few individuals within the company know how to handle them. In addition, every time you need a custom report you have to rely on your tech-skilled colleagues.

By creating a personalized Business Intelligence solution, many key people throughout an organization can gain easy access to understandable and meaningful data. Research has shown that organizations that democratize the use of these tools across the business by making them more user-friendly achieve a significantly higher ROI.

7. Limited Access to Data

Mobile devices are omnipresent in our daily lives and are changing the way we do business. Why not use them to make a better decision faster? With a BI solution, everyone in the organization, including managers, senior executives, and functional teams, can access and analyze up-to-date information when they need it, wherever they are, on a range of different devices.

You can share information efficiently and effectively with people across your organization and make better decisions.

We’ve never had such advanced technology as we do today. It would be a great loss not to take advantage of as much of this as possible, especially in today’s economic environment where the competition is strong and clients are more demanding.

A business intelligence solution can help a team identify new growth opportunities – for now and in the future – and take advantage of meaningful data that can help it prosper, even in a difficult and uncertain economic situation.

What Companies Use Business Intelligence?

Here are 5 real-world examples of business intelligence platforms in action.

1. HelloFresh centralized digital marketing reporting to increase conversions

Company: HelloFresh
Problem: Digital marketing reporting was time-intensive, manual, and inefficient.
Solution: For meal kit company HelloFresh, a centralized business intelligence solution saved the marketing analytics team 10-20 working hours per day by automating reporting processes. It also empowered the larger marketing team to craft regional, individualized digital marketing campaigns.

Based on aggregate analyses of customer behavior, HelloFresh created three buyer personas to guide their efforts. Being able to see and track real-time data means the team can react to customer behaviors and optimize marketing campaigns. As a result, they saw increased conversion rates and improved customer retention.

2. REI increased membership rates for co-op retailer

Company: REI
Problem: Difficulty tracking membership metrics with 90 terabytes of data.
Solution: In this example, Outdoor retail co-op REI uses a business intelligence platform to analyze their co-op membership. Co-op members contribute to REI’s account for more than 90 percent of purchases with the retailer, so it is critical to track metrics like acquisition, retention, and reactivation.

All of this information equates to over 90 terabytes of data. The ability to parse all of this data means that operations teams can determine whether to invest more in brick-and-mortar retail or digital experiences for their members.

This leads to greater customer satisfaction and positive associations with the brand.
“We’ve seen a complete turnaround in 2017 with new member acquisition,” observed Clinton Fowler, Director of Customer and Advanced Analytics at REI.

The team also uses their BI platform to analyze customer segmentation, which helps inform decisions like shipping methods, member lifecycle management, and product category assortments.

3. Coca-Cola Bottling Company maximized operational efficiency

Company: Coca-Cola Bottling Company (CCBC), Coca Cola’s largest independent bottling partner
Problem: Manual reporting processes restricted access to real-time sales and operations data.
Solution: Coca-Cola’s business intelligence team handles reporting for all sales and delivery operations at the company. With their BI platform, the team automated manual reporting processes, saving over 260 hours a year—more than six 40-hour work weeks.

Report automation and other enterprise system integrations put customer relationship management (CRM) data back into the hands of sales teams in the field through mobile dashboards that provide timely, actionable information and a distinct competitive advantage.

A self-service BI implementation fosters more effective collaborations between IT and business users that maximize the expertise of participants. Analysts and IT can focus on big-picture strategy and long-term innovations such as enterprise data governance rather than manual research and reporting tasks.

4. Chipotle created a unified view of restaurant operations

Company: Chipotle
Problem: Disparate data sources hindered teams from seeing a unified view of restaurants.
Solution: Chipotle Mexican Grill is an American restaurant chain with more than 2,400 locations worldwide. Chipotle retired their traditional BI solution for a modern, self-service BI platform. This allowed them to create a centralized view of operations so they can track restaurant operational effectiveness at a national scale.

Now that staff have more access to data, the speed of report delivery for strategic projects has tripled from quarterly to monthly and saved thousands of hours. “This was the ticket to take all metrics and understanding to that next level,” explained Zach Sippl, Director of Business Intelligence.

5. Des Moines Public Schools identifies and helps at-risk students

Organization: Des Moines Public Schools
Problem: Manual Excel reporting meant administrators couldn’t see up-to-date data like attendance, preventing timely intervention.
Solution: Des Moines Public Schools (DMPS) used advanced analytics to improve dropout intervention rates and better understand the impact of various teaching methods on individual student outcomes.

The DMPS Research and Data Management team used a multiple linear regression model—nicknamed the dropout coefficient—to weigh student indicators to predict which students might be at risk of dropping out of school. They used a business intelligence platform to leverage the model. Data visualization made it easy for staff to identify individual, at-risk students and get those students the attention they need.

Dashboards set up by the Research and Data Management Team delivered real-time analytics to 7,000 DMPS teachers and staff so they could adapt and intervene sooner, dramatically improving the intervention success rates. The real-time analytics were supported by five years of historical data. This meant that staff could dig into historical data on the spot to validate insights on current students.

How do You do Business Intelligence?

Business intelligence can help companies make better decisions by showing present and historical data within their business context. Analysts can leverage BI to provide performance and competitor benchmarks to make the organization run smoother and more efficiently. Analysts can also more easily spot market trends to increase sales or revenue. Used effectively, the right data can help with anything from compliance to hiring efforts.
A few ways that business intelligence can help companies make smarter, data-driven decisions:

• Identify ways to increase profit
• Analyze customer behavior
• Compare data with competitors
• Track performance
• Optimize operations
• Predict success
• Spot market trends
• Discover issues or problems

Here are the steps:

Step 1) Raw Data from corporate databases is extracted. The data could be spread across multiple systems heterogeneous systems.

Step 2) The data is cleaned and transformed into the data warehouse. The table can be linked, and data cubes are formed.

Step 3) Using BI system the user can ask quires, request ad-hoc reports or conduct any other analysis.

What Skills Are Needed For Business Intelligence?

The specific BI skills necessary for a career in the field vary according to whether you want to be more of a back-end or a front-end BI professional. To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools.

• Data Analysis. Most BI skills and intelligence analyst-related skills are about using data to make better decisions. You need to be good at examining many different sources of data and then making accurate conclusions about them.
• Problem-solving. BI isn’t just about analyzing data; it’s also about creating business strategies and solving real-world business problems with that data. For example, you could be the one to extract actionable insights from specific retail KPIs that need to be visualized and presented during a meeting.
• Specific industry knowledge. While some of this can and will be learned on the job, you need to have a solid grasp of the industry’s dynamics, particularly the areas of the field that you’re looking to work in. Over time, you’ll want to become an expert in your industry as this will increase your ability to connect data with business problem-solving.
• Communication skills. In addition to acquiring intelligence analyst-related skills, you’ll need to be able to communicate your findings effectively to the other professionals you’ll be working with. To some extent, if you work in back-end BI, you won’t need to communicate quite as much. However, if you work in front-end, you’ll be responsible for communicating technical concepts to non-technical people. This kind of role requires excellent communication skills.
• Advanced vision and attention to detail. By its very nature, a career in business intelligence is incredibly detail-oriented. As a BI analyst or developer, you’ll often work with the smallest fragment of information with the objective of turning it into actionable insight. You will need a great deal of forward-thinking vision and the ability to pay very close attention to detail to succeed in the fast-paced world of BI.
• Business acumen. Last but not least on our list of essential BI skills is a little something called business acumen. To thrive in a business intelligence career, you will need to possess a swift ability to understand your company’s business model and how to tailor your efforts to not only gain maximum value from your key performance indicators (and the KPI management process) but also make strategic decisions that will help your organization succeed on a continual basis.

Can Python be Used For Business Intelligence?

Python can be very easy to learn and apply to achieve data analysis. If you are thinking you don’t have prior knowledge of Python to start with data analysis. You need to change your mind first.

How much Python you need to understand to perform data analysis? There is no need for you to expertise in Python programming language to work with data sets.

Thus you need a basic knowledge of Python and need to learn Python libraries. Python libraries consist of several features which offer the user to evaluate and analyze the data sets and produce effective outcomes.

The Python programming language has turned into a robust and powerful tool for data analysis with the help of these libraries. The libraries which are used in DA are listed below:

1. NumPy:

NumPy is a fundamental package for the Python is used generally for scientific computing. With the use NumPy the object for multidimensional arrays, matrices and routines are introduced. These allow the developer in performing the task of advanced mathematical and statistical functions on those arrays and matrices with the minimum code as possible.

2. SciPy:

The SciPy is an open-source Python module which is a collection of mathematical algorithms built on NumPy data structures by adding sets of algorithms, patterns, and high-level commands. These are later used for manipulating and visualizing the data for the analytics process. This library usually helps in solving differential and integrals numerically, optimization and more.

3. Pandas:

Pandas library is used for data manipulation which is based on NumPy data structure. It also provides various functions in the analysis of finance, statistics, social sciences, and This library offers tools which can shape the raw data into useful datasets. It also provides several functions for accessing, indexing, merging or grouping data easily.

4. IPython:

IPython is a higher version of the Python interpreter which provides great features to data scientists. It helps in creating clean and clear reports and statistics for the data analysis. IPython is also an embeddable interpreter for the programs.

5. Matplotlib:

Matplotlib library is used in Python to create graphs and visual representation of the data. It creates interactive 2D and 3D plots which can be very easily You can easily create a graph with little commands and is very flexible to work with statistical analysis.

These libraries will enable the user to handle the raw, incomplete, big data or datasets with less effort. There is no limit to size which you can analyze using Python libraries.

To perform data analysis with Python you need to import Python module i.e. Pandas. Pandas is a software module written for Python programming language which is used for data manipulation and data analysis.

Is Business Intelligence a Good Career?

Here are our top five reasons why you should pursue a career in BI.

1. Job security 

With organisations becoming more data-centric every day, BI consultants have become a sought-after asset to businesses. A role within the Business Intelligence field is relevant to every industry, as it is a medium between technological understanding and business thinking.

FDM’s BI Consultants are the link between business users and the data itself, helping stakeholders to interpret structured and unstructured data and make better decisions.

As the volume of data becoming available to organisations is ever-growing, so is the need for professionals who can understand and interpret it. Therefore, roles within Business Intelligence and data are set to become more and more in demand as they are crucial to making business operations smarter and more profitable.

2. Exciting career opportunities

Pursuing a position within Business Intelligence presents many opportunities for a satisfying and exciting career. BI consultants are essential for decision making on all levels within companies and are highly valued by senior stakeholders. With the insights they derive from data, BI professionals reveal trends, opportunities, problem areas and information that shapes the future of businesses.

Business Intelligence consultants often work on exciting projects towards the development of new technologies or organisational strategies. Many of our clients are financial institutions who take their data very seriously. At FDM, we have consultants working for major European banks as data stewards and visualisation tool experts, but we also have non-finance related placements.

For instance, we’ve partnered with a power station client to work on a new project where our BI consultants help gather a vast array of data, from weather forecasts to social event information, so that the power station is able to make intelligent predictions on the level of power demand on any given day.

On another exciting project, our consultants have supported a client in the media sector, working on an international digital advertising platform.

 3. Career paths and job prospects within BI

The FDM Academy provides the fundamentals of BI concepts and uses industry standard Microsoft tools to teach them in action. Once you have completed your training, you will have the basis and the knowledge to pursue a career in BI across a variety of job prospects depending on your skills and interests.

Once you have reached two to four years of experience, you can easily move on to a more senior role managing your own teams and projects, such as Head of BI or Data Insight. Here are some of the most common roles within BI:

• Business Intelligence Analyst is responsible for the understanding of large sets of organizational data. They develop business processes and strategies based on their findings.
  
• Business Intelligence Developer is more technical. They are responsible for the building and/or improving of BI solutions and transforming source data into consistent formats ready for dashboards and reporting. They are also responsible for managing database applications.
  
• BI Engineer works together with BI Analysts and Developers as well as clients, customers and various internal departments. Their job involves the improvement of data-based processes and tools as well as their implementation.
  
• Business Intelligence Project Manager is accountable for the successful delivery of a variety of projects, including the coordination of a team to successfully build and deploy data warehouses, portals, apps and other BI-reporting deliverables.

Other roles can include SQL Server Business Intelligence Developer, BI Semantic Model Developer, Data Analyst and more.

4. Opportunities for personal development

Organisations have realised the benefits of BI and those practices are now applied in every industry, from IT and software to healthcare, retail and government projects. This gives our consultants the opportunity to pursue a BI role from a range of areas or industries that they have personal interest in.

Our BI training teaches our consultants how to use popular industry tools. However, these tools are constantly evolving and changing, and it is very likely that you will have to learn new tools and constantly challenge yourself to stay ahead of industry trends.

5. You don’t need to have a technical background to be successful in BI  

In order to launch your career in BI, you don’t necessarily need a background in IT. You already have some of the most important skills and qualities required from your university or work experience that can be easily applied to a career in IT. Some examples are:

• Communication skills in order to understand requirements and present finding to business users
• Teamwork skills and the ability to cooperate with others
• Problem solving and ability to work under pressure
• Attention to details

BI consultants are the links between business users and the data, and therefore you must have a passion for IT and data as well as the ability to learn SQL, databases and other technologies needed to perform the duties of a BI Consultant.

Is Excel a Business Intelligence Tool?

With the right access to data, Excel can become an outstanding Business Intelligence (BI) system.

Business Intelligence (BI) is the systematic use of information about your company and its business environment to analyze, report, predict, and manage business performance.

Some would say that this definition describes what Excel has always done for business. But Excel users know that’s not true. Historically, Excel has had two significant limitations that have kept it from serving as a true BI tool.

First, Excel isn’t known for its ability to generate easy-to-read reports and analyses. But Excel can do a great job with dashboards. The interactive Recession Watch dashboard updates in about 15 seconds, and the Morning Update report updates in about seven seconds. Both download economic data from the Web.

The second limitation, however, is that native Excel handled data poorly…until quite recently.

But now, Excel can use Power Query to query data found in more than a hundred sources, and import that data into Excel Tables, Power Pivot, or both. And then we can use formulas to stage the data for charts, tables, and other presentations.

What is The Most Popular Business Intelligence Software?

1. Datapine

datapine is a BI software that lets you connect your data from various sources and analyze with advanced analytics features (including predictive). With your analysis, you can create a powerful business dashboard (or several), generate standard or customized reports or incorporate intelligent alerts to get notified of anomalies and targets.

This tool, rated with outstanding 4.8 stars on Capterra, is a powerful solution for businesses of all sizes since datapine can be implemented for various industries, functions, and platforms, no matter the size.

The tool offers features for both advanced users such as data analysts and average business users. The SQL mode enables analysts to create their own queries while, on the other hand, the intuitive drag-and-drop interface ensures a visually intuitive way of entering your values and creating powerful charts and dashboards, simply by using effective visual analytics.

2. SAS Business Intelligence

SAS Business Intelligence is a software solution offering numerous products and technologies for data scientists, text analysists, data engineers, forecasting analysts, econometricians, and optimization modelers, among others.

Founded in the 70s, SAS Business Intelligence enjoys a long tradition in the market, building and expanding its products every year. With a Capterra rating of 4.3*, this software enjoys a decent level of users’ trust and satisfaction.

3. Clear Analytics

Clear Analytics is a tool that consolidates data from internal systems, cloud, accounting, CRM, and allows you to drag-and-drop that data into Excel. It works with Microsoft Power BI, using Power Query and Power Pivot to clean and model different datasets. Capterra gives a high user review of 4.5 stars making this tool also one of the highest-rated on our list.

4. SAP BusinessObjects

SAP BusinessObjects is a business intelligence suite designed for comprehensive reporting, analysis, and data visualization. They provide Office integrations with Excel and PowerPoint where you can create live presentations and hybrid analytics that connects to their on-premise and cloud SAP systems.

They’re focused on business categories such as CRM and customer experience, ERP and digital core, HR and people engagement, digital supply chain, and many more. To be accurate, more than 170M users leverage SAP across the world, making it one of the largest software suppliers in the world. On Capterra, the company obtained a review of 4.2 stars, confirming its well-established place in the market since 1972.

5. Domo

Domo is a BI solution comprised of multiple systems that are featured in this platform, starting with connecting the data, and finishing with extending data with pre-built and custom apps from the Domo Appstore. You can use Domo also for your data lakes, warehouses, and ETL tools, alongside with R or Python scripts to prepare data for predictive modeling.

Similar to other tools, you can connect the data across your enterprise, utilize their machine learning and artificial intelligence capabilities while enabling users to explore the data on their own. With a firm 4.2 stars rating on Capterra, this BI platform is also recommended by many users across the world, despite the fact that the company is one of the younger on our list – founded in 2011.

What Are The Main Components of Business Intelligence?

The five primary components of BI include:

OLAP (Online Analytical Processing)

This component of BI allows executives to sort and select aggregates of data for strategic monitoring. With the help of specific software products, a certification in business intelligence helps business owners can use data to make adjustments to overall business processes.

Advanced Analytics or Corporate Performance Management (CPM)

This set of tools allows business leaders to look at the statistics of certain products or services. For instance, a fast food chain may analyze the sale of certain items and make local, regional and national modifications on menu board offerings as a result. The data could also be used to predict in which markets a new product may have the best success.

Real-time BI

In a mobile society, this particular component of BI is becoming increasingly popular. Using software applications, a business can respond to real-time trends in email, messaging systems or even digital displays. Because it’s all in real-time, an entrepreneur can announce special offers that take advantage of what’s going on in the immediate.

Marketing professionals can use data to craft creative limited-time specials such as a coupon for hot soup on a cold day. CEO’s may be interested in tracking the time of day and location of customers as they interact with a website so marketing can offer special promotions in real-time while the client is engaged on the website.

Data Warehousing

Data warehousing lets business leaders sift through subsets of data and examine interrelated components that can help drive business. Looking at sales data over several years can help improve product development or tailor seasonal offerings. Data warehousing can also be used to look at the statistics of business processes including how they relate to one another.

For instance, business owners can compare shipping times in different facilities to look at which processes and teams work most efficiently. Data warehousing also involves storing huge amounts of data in ways that are beneficial to different divisions within the company.

Data Sources

This component of BI involves various forms of stored data. It’s about taking the raw data and using software applications to create meaningful data sources that each division can use to positively impact business. BI analysts using this strategy may create data tools that allow data to be put into a large cache of spreadsheets, pie charts, tables or graphs that can be used for a variety of business purposes.

For example, data can be used to create presentations that help to structure attainable team goals. Looking at the strategic aspect of data sources can also help organizations make fact-driven decisions that take into account a more holistic view of the needs of the company.

What Are Examples of Business Intelligence Tools?

1. SAP Business Objects

SAP Business Objects is a business intelligence software which offers comprehesive reporting, analysis and interactive data visualisation. The platform focuses heavily on caterogies such as Customer Experience (CX) and CRM, digital supply chain, ERP and more.

2. Datapine

Datapine is an all-in-one business intelligence platform that facilitates the complex process of data analytics even for non-technical users.

Thanks to a comprehensive self-service analytics approach, datapine’s solution enables data analysts and business users alike to easily integrate different data sources, perform advanced data analysis, build interactive business dashboards and generate actionable business insights.

3. MicroStrategy

MicroStrategy is an enterprise business intelligence tool that offers powerful (and high speed) dashboarding and data analytics, cloud solutions and hyperintelligence. With this solution, users can identify trends, recognise new opportunities, improve productivity and more.

Users can also connect to one or various sources, whether the incoming data is from a spreadsheet, cloud-based or enterprise data software. It can be accessed from your desktop or via mobile. Setup, however can involve multiple parties and some rather extensive knowledge of the application in order to get started.

4. SAS Business Intelligence

While SAS’ most popular offering is its advanced predictive analytics, it also provides a great business intelligence platform. This well-seasoned self-service tool, which was founded back in the 1970s, allows users to leverage data and metrics to make informed decisions about their business.

Using their set of APIs, users are provided with lots of customisation options, and SAS ensures high-level data integration and advanced analytics & reporting. They also have a great text analytics feature to give you more contextual insights into your data.

5. Yellowfin BI

Yellowfin BI is a business intelligence tool and ‘end-to-end’ analytics platform that combines visualisation, machine learning, and collaboration. You can also easily filter through tons of data with intuitive filtering (e.g. checkboxes and radio buttons) as well open up dashboards just about anywhere (thanks to this tool’s flexibility in accessibility (mobile, webpage, etc.).

The nice thing about this BI tool is that you can easily take dashboards and visualisations to the next level using a no code/low code development environment.

How Can Business Intelligence Help an Organization?

The major benefits that business intelligence provides are directly derived from the purpose it serves in the modern business scenario. Business intelligence helps in:

• Accelerating decision-making process
• Optimizing internal business processes
• Increasing the operational efficiency
• Driving revenues
• Gaining competitive advantages
• Identifying the market trends
• Spotting addressable business problems

The major issue in the modern business scenario is that business owners often mix business analytics with business intelligence. A business owner must understand that the core of BI is reporting not process management. Business intelligence has the power of transforming organizations.

How Walmart Uses Business Intelligence?

Walmart uses business intelligence to encourage customers by giving discounts and offering promotional plans. In general, Walmart’s smartphone apps, its websites, servers, software, and applications collect significant amount of data to do business in efficient way and to gain more consumers.

How Does Netflix Use Business Intelligence?

Netflix uses data processing software and traditional business intelligence tools such as Hadoop and Teradata, as well as its own open-source solutions such as Lipstick and Genie, to gather, store, and process massive amounts of information. These platforms influence its decisions on what content to create and promote to viewers.

Netflix doesn’t use a traditional data center-based Hadoop data warehouse. In order to allow it to store and process a rapidly increasing data set, it uses Amazon’s S3 to warehouse its data, allowing it to spin up multiple Hadoop clusters for different workloads accessing the same data. In the Hadoop ecosystem, it uses Hive for ad hoc queries and analytics and Pig for ETL (extract, transform, load), and algorithms.

It then created its own Genie project to help handle increasingly massive data volumes as it scales. All this points to one thing: Netflix is very particular about having a lot of data and being able to process this data to ensure it understands exactly what its users want.

The result has been nothing short of amazing. Netflix has been able to ensure a high engagement rate with its original content, such that 90 percent of Netflix users have engaged with its original content.

Netflix’s big data approach to content is so successful that, compared to the TV industry, where just 35 percent of shows are renewed past their first season, Netflix renews 93 percent of its original series.

What is Business Intelligence Tools?

Business intelligence (BI) tools are types of application software that collect and process large amounts of unstructured data from internal and external systems, including books, journals, documents, health records, images, files, email, video, and other business sources. While not as flexible as business analytics tools, BI tools provide a way of amassing data to find information primarily through queries.

These tools also help prepare data for analysis so that you can create reports, dashboards, and data visualizations. The results give both employees and managers the power to accelerate and improve decision making, increase operational efficiency, pinpoint new revenue potentials, identify market trends, report genuine KPIs, and identify new business opportunities.

Typically used for more straightforward querying and reporting of business data, business intelligence tools can combine a broad set of data analysis applications including ad hoc analysis and querying, enterprise reporting, online analytical processing (OLAP), mobile BI, real-time BI, operational BI, cloud and software as a service BI, open-source BI, collaborative BI, and location intelligence.

It can also include data visualization software for designing charts, as well as tools for building BI dashboards and performance scorecards that display business metrics and KPIs to bring company data to life in easy-to-understand visuals.

Importance of Business Intelligence

Why is Business Intelligence so important to modern-day organizations? The main reasons to invest in a solid BI strategy and system are:

Gain New Customer Insights: One of the primary reasons companies are investing their time, money, and efforts into Business Intelligence is because it gives them a greater ability to observe and analyze current customer buying trends.

Once you utilize BI to understand what your consumers are buying and the buying motive, you can use this information to create products and product improvements to meet their expectations and needs and, as a result, improve your organization’s bottom-line.

Improved Visibility: Business Intelligent organizations have better control over their processes and standard operating procedures, as the visibility of these functions is improved by a BI system. The days of skimming through hundreds of pages of annual reports to assess performance are long gone.

Business Intelligence illuminates all areas of your organization helps you to readily identify areas for improvement and allow you to be prepared instead of reactive.

Actionable Information: An effective Business Intelligence system serves as a means to identify key organizational patterns and trends. A BI system also allows you to understand the implications of various organizational processes and changes, allowing you to make informed decisions and act accordingly.

Efficiency Improvements: BI Systems help improve organizational efficiency which consequently increases productivity and can potentially increase revenue. Business Intelligence systems allow businesses to share vital information across departments with ease, saving time on reporting, data extraction, and data interpretation.

Making the sharing of information easier and more efficient permits organizations to eliminate redundant roles and duties, allowing the employees to focus on their work instead of focusing on processing data.

Sales Insight: Sales and marketing teams alike want to keep track of their customers, and most utilize Customer Relationship Management (CRM) application to do so. CRMs are designed to handle all interactions with customers.

Because they house all customer communications and interactions, there is a wealth of data and information that can be interpreted and used to strategic initiatives. BI systems help organizations with everything from identifying new customers, tracking and retaining existing ones, and providing post-sale services.

Real-Time Data: When executives and decision-makers have to wait for reports to be compiled by various departments, the data is prone to human error and is at risk of being outdated before it’s even submitted for review.

BI systems provide users with access to data in real-time through various means including spreadsheets, visual dashboards, and scheduled emails. Large amounts can be assimilated, interpreted, and distributed quickly and accurately when leveraging Business Intelligence tools.

Competitive Advantage: In addition to all of these great benefits, Business Intelligence can help you gain insight into what your competitors are doing, allowing your organization to make educated decisions and plan for future endeavors.

Benefits of Business Intelligence

Business intelligence is more than just software. It’s a holistic initiative to use data in day-to-day operations. The 7 benefits below translate into real-world success that showcases BI in action.

1. Faster analysis, intuitive dashboards

BI platforms are designed to do heavy-duty processing of data in the cloud or on your company’s servers. BI tools pull in data from multiple sources into a data warehouse, and then analyzes the data according to user queries, drag-and-drop reports, and dashboards.

Business intelligence helped Lenovo increase reporting efficiency by 95 percent across several departments. Their HR department condensed several monthly reports to a single snapshot dashboard. PepsiCo also cut analysis time up to 90 percent through the power of BI.

The benefit of business intelligence dashboards is making data analysis easier and intuitive, empowering non-technical users to tell stories with data without having to learn code.

2. Increased organizational efficiency

BI provides leaders the ability to access data and gain a holistic view of their operations, and the ability to benchmark results against the larger organization. With a holistic view of the organization, leaders can identify areas of opportunity.

Pfizer uses BI platforms to collaborate among departments and developed models to optimize patient diagnosis and faster, better ways to perform clinical trials. Insurance company PEMCO used Tableau in their operations to manage and close claims fast.

When organizations spend fewer hours on data analysis and compiling reports, BI gives them more time to use data to innovate on new programs and products for their business.

3. Data-driven business decisions

Having accurate data and faster reporting capability provides for better business decisions. MillerCoors customized mobile dashboards for their sales team so they can view real-time data and sales forecasts before going into meetings with potential clients.

They can speak of clients’ or prospects’ needs confidently and know the data is up-to-date. No longer do leaders have to wait days or weeks for reports and deal with the risk of data that may be outdated.

4. Improved customer experience

Business intelligence can directly impact customer experience and customer satisfaction. Verizon deployed BI systems across multiple departments, creating more than 1,500 dashboards for employees.

These dashboards pulled data from operations and text data from customer support chat sessions. Using this data, Verizon was able to identify opportunities to improve customer service and reduce support calls by 43 percent.

5. Improved employee satisfaction

IT departments and analysts spend less time responding to business user requests. Departments who didn’t have access to their own data without contacting analysts or IT can now jump into data analysis with little training.

BI is designed to be scalable, providing data solutions to departments who need it and for employees who crave data. BrownForman scaled Tableau to 1,000 global users, and found that it fit well within their existing data infrastructure. BI software should have a seamless and intuitive user experience for non-technical users to look at data.

6. Trusted and governed data

BI systems enhance data organization and analysis. In traditional data analysis, different departments’ data is siloed and users have to access several databases to answer their reporting questions.

Now, modern BI platforms can combine all of these internal databases with external data sources such as customer data, social data, and even historical weather data into one data warehouse. Departments across an organization can access the same data at one time.

Marketing agency Tinuiti centralized over 100 data sources using business intelligence technology, saving their clients hundreds of hours of analysis time.

7. Increased competitive advantage

Organizations can be more competitive when they know the market and their performance within the market. Rosenblatt Securities analyzed data from hundreds of sources and was able to see the best possible time to enter and exit the market and position themselves strategically. With BI, businesses can keep up with changes in the industry, monitor seasonal changes in the market, and anticipate customer needs.

Sources of Business Intelligence

Businesses digitally store a tremendous amount of operational data, and for business intelligence to function, it needs wide-open roads between data sources.

Mainframe legacy systems still form the foundation of many companies’ data centers because of their ability to process and harbor huge quantities of data, but their data is notoriously difficult to get to as many of the legacy applications are obsolete, proprietary, or pre-standards software. Other options for data sources are:

Enterprise Resource Planning (ERP): Often implemented throughout the organization in modules that map to specific business domains, such as supply-chain, human resources, finance, accounts payable, and so on. ERP systems store a lot of transactional data used in today’s BI environments.

Customer Relationship Management: A common data source for business intelligence, CRM systems do just what they say: they process and store customer profile and behavior information, like purchase activity.

E-Commerce: Web applications can act as source data systems for business intelligence platforms by feeding real-time sales activity.

Use of Business Intelligence

Business intelligence involves the use of computing technologies to identify, discover and analyze business data to provide not only the current but also the historical and predictive views of data. This makes it possible for decision-makers to access, analyze and understand business information so they can execute accordingly and drive their organizations forward.

To have and utilize business intelligence  – that is, to transform raw business data into useful information to drive increased revenue – you need appropriate BI tools. If you’ve previously operated on the belief that BI software is an unnecessary added expense, now is the time to reconsider.

In today’s data-driven climate, you stand to lose valuable opportunities without this software. Essentially, you’re putting the success of your organization on the line.

If you need still a bit more convincing, here are 10 things BI solutions can do for your organization.

Provide business information quickly and efficiently

Many business decisions need to be made on the spot, and to ensure sure you’re making the right one, you need access to information. Information isn’t just numbers in a column, but also what those numbers mean for your organization. Using BI software gives you this information at the click of a button to help you gain a competitive advantage.

Come up with performance indicators aligned with your business strategies

When companies focus on doing tasks that are not aligned with their strategy, this leads to both time and money wasted. To avoid this, you need to establish metrics that come with performance indicators that are aligned with your company strategies. BI tools can help you in this regard by providing the metrics so you can focus on improving performance where it really matters.

Empower employees through data access

BI solutions enable employees to make informed, data-driven decisions by giving them access to relevant, real-time data. This allows organizations to maximize information across all levels and empowers employees for professional and personal growth. Having an empowered workforce can make a company more competitive in the global business arena.

Save time on entering data and making reports

Manual data entry is prone to human error, even when it’s copied and pasted from another source. Not only that, it also takes a lot of time to do properly. By using a well-configured BI system, you eliminate time spent on data entry and decrease the amount of time spent on performing calculations.

BI tools also allow for quick report generation and data visualization where you can see all the information you need in one place. By saving time on creating reports, you can see how your business is doing and make profitable decisions quickly.

Gain more customer insights

Meeting customers’ needs is what drives businesses forward, which is why it’s important that you are able to discover patterns in customer behavior. Without BI tools, it is difficult to know what customers really want without spending hours upon hours poring over past reports. BI software allows you to identify which customers should be prioritized in order to increase customer satisfaction and improve your market reputation.

Show important information about your sales

One of the primary functions of BI applications is to reveal sales information, especially if you work with multiple sales partners. With BI on hand, your team is able to know which sales partners perform well and which need to exert more effort.

Identify areas where you can cut costs

BI software allows you to see which areas of your business you can save money on, such as inventory. There may be an excess in your inventory, which translates to extra costs not only in terms of acquisition, but also maintenance. Once you know where you can increase productivity and cut costs, you can take the necessary action to increase your savings.

Increase employee productivity

With BI tools, you are able to monitor the tasks, output and overall performance of your team. This enables you to identify where you can streamline work processes and make your operations more efficient, therefore increasing the productivity of your workforce.

Achieve greater social media intelligence

Organizations leverage social media to connect with existing and potential customers. You can use BI software to gain insights on consumer behavior and identify avenues for actively connecting with people to expand your customer base.

Protect your business from online threats

Data breach and malware attacks are some of the most common online threats to businesses, which is why it’s crucial to invest in BI solutions that are equipped with powerful analytics and advanced security tools. Top-notch BI software with security features is designed to help protect your organization from hackers and other malicious attacks.

Organizations big and small can greatly benefit from the use of BI solutions in all aspects of business – from budgeting to customer relations. All it takes is a little research to help you compare and choose the solution that will meet the needs of your business. With the right BI software, you can expect great advancements for your organization.

Is There Coding in Business Intelligence?

Business Intelligence (BI) requires programming skills for processing data to produce useful insights for a business in some stages of the BI project lifecycle such as the data modeling and warehousing stages. Coding may not be needed in the other stages. Anyone can start a career in BI with some practice of programming.

In the data modeling and data warehouse building stages of the Business Intelligence lifecycle, BI analysts typically spend a larger amount of time coding in SQL and Python or R. SQL or Structured Query Language is a common querying language used to speak to databases to retrieve the required information. Python and R are programming languages used for data transformation and processing.

it is possible to do business intelligence (BI) without programming. Some BI data visualization tools like Tableau and Power BI are no-code analytics solutions that do not require programming skills. Not all BI positions in companies do programming as well.

However, some knowledge of programming skills might be necessary when working with other stakeholders such as data scientists and data engineers.

Who Can Become Business Intelligence Analyst?

Business intelligence analysts help a company put the data it already collects to use in order to increase the company’s efficiency and maximize profits. They comb through large amounts of data by querying databases effectively, and then produce reports and identify trends to generate actionable business insights.

Business intelligence analysts must have a range of data analytics skills that serve them well in the world of big data, especially data analysis, as well as keen business understanding that is crucial in a field that hinges so heavily on soft skills like teamwork and polished communication skills in both the written and verbal realms.

Business intelligence analysts are a necessary part of making the extensive amount of data now available to companies useful. Business intelligence analysts straddle the worlds of business and information technology, having a firm grasp of each, and are able to mine and analyze data to recommend growth strategies for a company.  

Once a business intelligence analyst makes recommendations for technological advances in a company, they are often needed to lead seminars for colleagues, including training managers to implement and monitor these new systems.  

What does a Business Intelligence Analyst do? 

In the data science workforce of today, the business intelligence analyst evaluates both the data of the company itself as well as data from competitors and others in the industry, in order to discover ways to improve their own company’s market position. 

Good business intelligence analysts will look into their company’s systems, procedures, and functions, and find areas in which the company can increase efficiency and profit margins. 

Business intelligence analysts also must consider new ways in which a company can develop new policies regarding data collection and data analysis methodologies, including ensuring integrity of data use. Business intelligence analysts may also be charged with hiring other data specialists at times, such as data architects.

What Are The Types of Business Intelligence?

There is a cloud of debate among decision makers in business to choose the type of BI they should adopt. When managers have a good idea of what they wish to analyze sales figures or customer satisfaction stats but they are not aware of the end results then most preferred tool is strategic business intelligence.

When decision makers stand on the option they “don’t know” strategic BI is adopted. There are instances in a business organization where managers deliver anticipated information in such situations operational business intelligence is the best preferred over strategic intelligence. This is mainly because operational intelligence emphasizes on standard tasks that employees need to complete.

From an organization perspective, the identity and properties of task help the employee to complete the assigned work in a specific time frame. Consider an example of operational intelligence where an account manager in an organization makes an entry of a new order for the customer.

Most of the organization would like the account manager to know intelligence about the customer’s credit status and whether he has any overdue invoices.

Strategic Business Intelligence

Strategic Business Intelligence also known as auto-delivered intelligence is often associated with reporting from an analytical data source or data warehouse. Basically, strategic BI improves a business process by analyzing a predetermined set of data relevant to that process and provides historical context of data.  

In addition, strategic intelligence provides the base for forecasting, goal-setting, planning and direction. Strategic BI needs to be delivered in an interactive manner, enabling the manager to present his views on data in different ways.

Also, strategic business intelligence emphasizes on its output on a graphical display such as charts and graphs to represent trends, opportunities and problem areas. Strategic business intelligence converges on four important parameters:

•  Collection and storage of data

•  Optimisation of data for analysis

•  Identification of crucial business drivers through past data records

•  Seeking answers to key business questions

Operational Business Intelligence

Operational business intelligence is associated with the transactional or operational data source and is consistent with reporting data during organizational processes. In general, operational BI provides time-sensitive, relevant information to operations managers, business professionals, and front-line, customer-facing employees to support daily work processes.

Also if the data retrieved from the analysis directly supports or helps complete operational tasks, then the intelligence is operational in nature. But operational business intelligence demands recipients time as possible which iron out the information presented in an interactive manner. Since operational BI is task oriented there is less need of charts and graphs.

Consider an example informing a staff member in an organization regarding information on client’s credit or on over dues. In such a scenario graphical representation won’t hold good but a brief message wilFl solve the problem. Hence communication methods and devices play a vital role in operational BI.

Thus, operational BI comprises multiple delivery methods like instant message, email, dashboard and Twitter. The output from an operational business intelligence include invoices, schedules, shipping documents, receipts and financial statements.

What Are The Characteristics of Business Intelligence?

The most important business intelligence characteristics include:

1. Ranking Reports

Ranking reports let you easily view the best- and worst-performing facets of your business, from products to marketing campaigns to salespeople. You can view rankings across multiple dimensions and specify various criteria to focus your results.

2. What-If Analysis

If you’re curious about how a future decision will affect your business, you can run a “what-if” analysis using past data to predict the potential impacts. Tools for what-if analyses give you an objective view of the risks and rewards involved in each potential decision, and allow you to plan better for the future.

3. Executive Dashboards

Executive dashboards give your organization’s leaders a real-time overview of your business in the form of graphs, charts, summaries and other information reports. They allow your company’s executives to make smarter, faster and better decisions.

4. Interactive Reports

Interactive reports allow users to condense the massive amounts of collected data into a wide variety of possible views. Users can take advantages of features like statistical analysis and regression to identify trends, anomalies and outliers in the data.

5. Geospatial Mapping

Applications using location intelligence can take your information and transform it into graphical and cartographic representations, simplifying your geographical data. At a glance, judging which regions are performing better than others — and which ones need particular attention — becomes much easier.

6. Operational Reports

At the end of each day, business intelligence features like these can provide your organization’s executives with a detailed summary of the daily events, giving them the information they need to make critical decisions.

7. Pivot Tables

Pivot tables can automatically extract significant features from a large, messy set of data. They can perform calculations such as sorting, counting or averaging the data stored in one table, and show the summarized results in another table. Pivot tables are essential tools for analyzing information and uncovering hidden trends.

8. Ad-Hoc Reports

Instead of burdening your IT department with requests for detailed reports, ad-hoc reports are one of several important features of BI that let your nontechnical end-users generate their own reports on the fly. Users can pick and choose the elements that they wish to be included in the report, emphasizing only those aspects that are relevant to their query.

9. User-Specific Security

If you need to restrict certain users’ access to particular data sets, your BI tool should allow you to personalize your BI features and applications to individuals or groups of users. Some solutions provide user-specific data sources, where a single application pulls from different sources of data depending on who’s using the application.

10. Open Integration

Smart BI platforms will be able to access not only your organization’s own data, but information from email, social media, websites and more. For example, instead of only providing your internal sales data, your BI platform could accompany that information with reviews and comments about your products.

Which Language is Used For Business Intelligence?

There are approximately 700 programming languages out there. While all of them can prove useful in some aspects, not all of them are suitable for business uses. That’s why we decided to bring out the list of coding languages used in the business intelligence.

Let’s take a closer look at the nine best programming languages for business.

Java

Java is one of the oldest coding languages. Since the inception of Java, programming has developed dramatically. It continues to be widely used by custom software development companies. However, contrary to the belief that this programming language is mostly used in the IT field, it’s also used in the business one. Many Java features make this particular language especially suitable for business usage.

Portability, scalability, being multi-threading, efficiency, security, and its compatibility with Android, make Java highly relevant and useful in the business field.

Python

Python continues to lead the lists of the most used and loved programming languages, even in 2020. Python offers a great variety of open-source libraries for data science, image recognition, and many others. It’s widely used by web applications such as Youtube, Pinterest, and Instagram.

Among the reasons why Python can be useful in your business undertakings are: free to use, easy to use,  efficient communication of Python with other languages and platforms, extensibility, and scalability.

JavaScript

Where there is Java, certainly, there will also be JavaScript. What differentiates JavaScript from other programming languages is that it’s a front-end language. It’s mostly used to build front-end interactive applications.

The thing that makes this language useful in the business field is the efficiency of running client-side and server-side scripts. It can be used to create web page content before actually transferring it to a web browser. Its speed, high-quality control, and its frameworks are some of the advantages of JavaScript.

C/C++

C++ is a general-purpose and one of the classic coding languages. This particular coding language is used in many different areas, such as operating systems, database management systems, medical applications, and many more, but mostly it’s used in systems programming and embedded systems.

What makes C++ useful for business is its portability as it can be used in all operating systems without errors, its object-oriented structure because it offers reliability and options of reuse and functional libraries that make it possible to build network applications and countless other projects.

Go Programming Language

Go—the newest open-source programming language. Go, or Golang, is a static language as it holds testing tools and garbage collection. This way, making the programmers’ job easier as they won’t have to worry about memory management.

Like any other programming language, Go has some features that distinguish it from others. Those features are the simplicity due to the language being quite simple and scalable, and the built-in testing feature that makes it possible for developers to conduct hundreds of automated tests monthly.

PHP

PHP is an intuitive server-side, open-source programming language and one of the leading languages used for web development. There are many reasons why developers and businesses choose PHP for IT solutions. The first one is that PHP is flexible. What do we mean by this? PHP can be used in numerous platforms such as Microsoft, UNIX, Linux, etc. This language supports almost all servers and databases.

Another reason is that PHP is budget-friendly. It doesn’t require any fees or downloading because it’s distributed under the General Public License. PHP is also a great web hosting option. That’s why many agencies provide plans on websites supported by PHP.

Swift

Swift is one of the latest programming languages that joined the development scene. It was created by Apple, but soon they open-sourced its code. Swift is a fast and interactive, open-source coding language. It’s mostly used to develop apps for the whole Apple ecosystem. Among the advantages of this programming language is the speed which is 2 times faster than Objective-C programming.

C#

C# is considered a hybrid of C and C++ and is quite similar to the programming languages as Java, C, and JavaScript, even though it was initially created to compete with Java. The syntax of C# is quite simple and easy to understand. C# is mostly used to develop applications and games for desktops. 

The reason why C# got popular in the first place is that it’s easy to learn and it’s versatile, meaning that you can do almost anything using it, starting with desktop apps, mobile apps, web applications, etc.

Ruby

Ruby is one of the 12 most functional programming languages. It’s an object-oriented, dynamically typed, and open-source coding language. Because of its features, Ruby is mostly used for back-end development. Ruby has some advantages over other coding skills when it comes to business—a strong focus on testing, stability, and predictability, and time efficiency are just some of them.

The world of programming is ever-changing. New and better programming languages could always be developed in the future that could better assist you in your business. Until then, this list will give you an idea of what coding languages are available for you to learn and the enterprises to leverage.

How do I Start a Business Intelligence Career?

Follow these steps to become a business intelligence analyst:

1. Earn a degree

The first step toward becoming a business intelligence analyst is to complete a four-year bachelor’s degree program. Common majors for business intelligence analysts include computer science, data science, statistics, business administration, economics and related fields.

Regardless of the major you choose, coursework in areas related to statistics, technology and data analysis are beneficial to the role of a business intelligence analyst.

2. Complete an internship

Many bachelor’s degree programs offer an opportunity to complete an internship program in the field of business or specific industries such as accounting. If you are interested in becoming a business intelligence analyst, completing an internship program can help you gain the relevant work experience you will need to qualify for the position and can help you begin to establish your professional network.

3. Consider professional certifications

There are many professional certifications you may consider obtaining to highlight your skills and knowledge in areas related to the role of a business intelligence analyst.

A few certifications you may want to consider include Microsoft’s Certified Solutions Expert in business intelligence certification, the Certified Business Intelligence Professional (CBIP) certification, computer programming and language certifications and business administration certifications. Some employers may require specific certifications to qualify for the role of a business intelligence analyst.

4. Consider an advanced degree

Many business intelligence analysts choose to continue their education to pursue a Master of Business Administration (MBA) degree or another master’s level degree program. Having a master’s degree can help open more career opportunities for business intelligence analysts and increase their earning potential. Some companies will even accept a master’s degree in lieu of additional relevant work experience for business intelligence analyst positions.

5. Gain more relevant experience, if needed

You should review the job requirements for the business intelligence analyst positions you are interested in to determine whether candidates need a certain amount of relevant work experience to qualify for the role.

Many businesses prefer business intelligence analyst candidates who have related work experience in information technology (IT), management or business. You may be able to gain the experience needed for the role of a business intelligence analyst through internship programs and entry-level positions within your industry such as a data analyst or business analyst.

6. Search for business intelligence analyst positions

Once you have obtained the necessary education, experience and certifications needed to qualify for the role of a business intelligence analyst, you are ready to begin looking for available positions to apply to.

Read Also: What is Qualified Business Income Deduction?

Review the job description for each position you are interested in applying to for information about the skills and qualifications the employer is looking for. You can also consider checking with your current employer to see if a position as a business intelligence analyst is available.

7. Prepare a resume and apply

Once you have found the business intelligence analyst positions you are interested in applying to, use the information you gathered from the job descriptions about the skills and qualifications the employer prefers candidates to have to create a resume that is customized to the position. You can use an online resume builder to help you target keywords from the job description when describing your experience and skills.

Once you have finished your resume, you can return to the original job posting and apply for the position you are interested in. If your current employer has a position for a business intelligence analyst available, you can provide your updated resume for consideration for a promotion.

Finally

Business Intelligence helps companies monitor trends, adapt to varying market conditions, and improves decision making at all levels of the organization. The BI tools a company uses depends on their goals.

Some companies are interested in gaining insights into consumer buying, other companies are interested in improving employee productivity or seeing who the best performers are. There are an infinite number of ways companies can deploy a business intelligence solution.