Today, big data is the lifeblood of most company operations. Companies in banking, retail, and technology have unparalleled access to data that can be used to optimize performance and influence decision making.

However, data only becomes a strategic asset when important information can be extracted from it. That is why you need data analytics to transform raw data into actionable insights that guide choices and produce positive business outcomes. Data analytics transforms our streaming choices into personalized recommendations, and our collective medical history into better patient care.

Of course, the volume and variety of data that we now deal with cannot be processed manually. Your organization will need to invest in the correct tools and software to truly harness the potential of complex data analytics and get a competitive edge in decision making.

Data analytics platforms are a collection of tools and services that help businesses collect, store, clean, organize, and model raw data. Modern platforms use machine learning and artificial intelligence to bring data analytics to new heights. A good platform would also feature data visualization tools for converting numbers into charts and graphics that can be used to effectively communicate findings to key stakeholders.

But how can you choose between the several data analytics tools on the market today? There are many more solutions available now, including (in no particular order) Microsoft Power BI, Sisense, Tableau, Qlik, SAP, SAS, and IBM Cognos Analytics.

Choosing the correct platform for your company is a difficult decision; frequently, the barriers to better data-driven efficiency are less about the technology available and more about how organizations implement it.

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So, here are some guidelines to assist you choose a data analytics platform that is a suitable fit for your business.

1. Business Objectives

Like any other IT investment, your analytics platform should support both your existing and future business requirements. First, you must identify the core objectives of your business and create a list of your desired business outcomes. Next, break down your business objectives into measurable analytics goals. Finally, choose an analytics platform that provides access to data and reporting features that can help you achieve these business objectives.

2. Pricing

Do you have the time, money, and expertise to build and maintain your own analytics solution? Before selecting an analytics tool, you must be fully aware of the costs associated with the analytics solutions you are evaluating – including subscriptions, growth, and hidden fees. Different analytics solutions have different cost structures and it is important to understand them before making an investment.

3. User Interface and Visualization

Your analytics tool is what your employees will refer to while making business decisions. Self-service analytics should have a user-friendly interface that can support different user types. Even non-technical users must find it easy to use and be able to create and understand dashboards and reports. While visuals may not seem too important, if your dashboards feature unappealing visuals, it will have a negative impact on user adoption.

4. Advanced Analytics

Your analytics application must be able to recognize patterns in data and predict future trends, events, and outcomes. It must go beyond simple mathematical calculations and generate contextualized insights giving you the ability to build advanced statistical models and future-proof your business.

5. Integration

While selecting your analytics tool, you must decide whether a standalone solution or an integrated solution is right for your business. You have a variety of options with standalone solutions but integrated solutions allow you to access analytics from applications that your users are already familiar with. You must understand how your analytics platform can connect with your existing systems and third-party data sources. You must also assess how easily you can move your data to other systems if the need arises.

6. Mobility

Mobile analytics is an easy and powerful way to keep everyone in your organization connected anywhere and at any time. Mobile analytical capability is critical for companies that operate globally to make data-driven decisions on the go. Before evaluating options, ask the following questions:

• What kind of mobile analytical capabilities do your employees need?
• Do they need to simply view dashboards and reports, or also create or edit them on-the-fly?

Mobile BI improves access to information, speeds up reaction times, and improves internal communication. Studies show that mobile BI also improves user adoption.

7. Agility and Scalability

Cloud-based analytics platforms are designed to start small and grow with your business. These pay-as-you-go plans can give early-stage businesses a competitive edge and support them when they are experiencing hyper-growth. You can get timely data access and insights to make fast decisions with analytics that scale according to your business needs.

8. Multiple Sources Of Data

Modern analytics tools can combine multiple sources of complex data, and analyze structured, semi-structured, and unstructured data. It’s important to select tools that don’t require assistance from your IT department. Having the ability to gather and combine data from different systems onto a single dashboard allows you to have a complete view of your business performance.

9. Customization

Every business has unique requirements, so you must select an analytics tool that meets your specific requirements. Your business might require a custom analytics set-up to integrate seamlessly into your operations. You must also assess whether the solution can be extended or altered to meet both current and future needs.

10. Collaboration

Self-service, collaborative analytics support brainstorming through social features and simplify the problem-solving process. Your analytics tool must allow users to share, analyze and interact with data in different content formats to enable smarter, collaborative decision making. You should be able to quickly distribute insights across your organization whenever you need to make to collaborate and make decisions.

11. Security

You must evaluate the security of your analytics provider and vendor to ensure that the necessary precautions are in place to safeguard your information. Set up standard security controls and procedures at all levels – process level, system level, and data level, to control precisely which users or groups can access which information. Also, it is important to understand the implications of mobile BI as users can access data wherever they are, outside of company firewalls.