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One of the most often used pieces of data analysis software is SAS (Statistical Analysis System). Data management, data mining, report authoring, statistical analysis, business modeling, application development, and data warehousing are just a few of the many uses for which it is frequently employed. SAS knowledge is useful in several job markets. Since its beginning eight years ago, it has been positioned as a “leader” in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms for Advanced Analytics Platforms.

SAS has over 40,000 customers worldwide and holds the largest market share in advanced analytics. It has been tagged ‘leader’ consistently for the last 6 consecutive years in advanced analytics platforms. In the finance (BFSI) industry, SAS retains the No. 1 spot and is being used as a primary tool for data manipulation and predictive modeling.

  • Data Security – Because of unparalleled data security provided by SAS software, it is leading the analytics software industry in BFSI sector.
  • Tech Customer Support – SAS provides one of the best tech support. If you are stuck in anything related to SAS whether it is installation related issue or clarity in any of SAS functions and procedures, they have both online and offline community to support you.
  • Detailed Documentation – SAS documentation is very detailed as compared to open source software like R and Python.
  • Memory Management – SAS can store datasets on hard drive and process bigger data set than size of your RAM.
  • Stable Software more important than cost of software license : All the functions and procedures of previous software version are supported in new SAS versions. Cost of software license is a peanut to a bank or pharmaceutical company.
  • Legacy System – Many banks have been using SAS for last 20-30 years and they have automated the whole process of analysis and have written millions of lines of working code. To convert all the stable reporting system from SAS to R/Python, it may require significant additional cost.

When you install SAS software, it has several in-built modules which are designed for various analytics and reporting purposes. See some of the common SAS modules or components.

  • Base SAS – It is the most common SAS module. It is used for data manipulation such as filtering data, selecting, renaming or removing columns, reshaping data etc.
  • SAS/STAT – It runs popular statistical techniques such as Hypothesis Testing, Linear and Logistic Regression, Principal Component Analysis etc.
  • SAS/ACCESS – It lets you to read data from databases such as Teradata, SQL Server, Oracle DB2 etc.
  • SAS/GRAPH – You can create simple and complex graphs using this component.
  • SAS/ETS – You can perform time series forecasting such as ARIMA, Exponential Smoothing, Moving Average etc. using this module.

Data analytics helps companies implement business models and reduce costs by identifying new trends and efficient ways to deliver better products and services.

Data analytics can be in 4 ways that are Descriptive analytics, Diagnostic analytics, Predictive analytics, prescriptive analytics, etc. Data analytics enables SAS experts to process structured or unstructured data to gain insights.

Data analytics allows the finance team to explore key metrics and spot fraud in revenue streams.

Data analytics Industry Sectors are- Finance and Banking, Telecommunications and Media, Sports, Healthcare and Pharmaceutical Organizations, Agriculture, Sports sectors, Education, Transportation, Manufacturing Industry, Energy and Utilities, Real Estate and property management, Government and public sector, Consumer Trade, etc.

SAS Data Management

SAS Data Management helps transform, integrate, govern, and secure data while improving its overall quality and reliability.

Read Also: How to Learn Data Analysis Faster?

Whether it’s traditional data in operational systems or big data in a Hadoop cluster, data is an asset that every organization has. And managing that data is no longer a convenience – it’s a necessity. SAS Data Management is the answer to solving your data integration and data quality challenges.

SAS Data Management is designed for IT organizations that need to address performance and functional improvements in their data management infrastructure.

With SAS Data Management, you can handle a wide variety of data challenges – from efficient processing of big data to accessing and integrating legacy sources – all in a single platform, with in-memory and in-database performance improvements helping to deliver trusted information.

SAS Visual Analytics

SAS Visual Analytics provides a modernized, unified environment for governed discovery and exploration. Users, including those without advanced analytical skills, can examine and understand patterns, trends, and relationships in data. It’s easy to create and share reports and dashboards that monitor business performance. Easy-to-use analytics and visualizations help everyone get insights from data to better solve complex business problems.

Users of all skill levels can visually explore data, use automated analysis and create visualizations while tapping into powerful in-memory technologies for faster computations and discoveries. This self-service solution scales to an enterprise-wide level, putting data and analytics in the hands of more people. At the same time, governance capabilities help IT promote consistency and reuse.

It’s designed for anyone in an organization who wants to create, share and collaborate on insights from data. That includes decision makers, business analysts, report creators, and citizen data scientists. It also provides IT with an easy way to govern and manage data integrity and security.

SAS Visual statistics

SAS Visual Statistics helps you get predicted values from the predictive models. It requires SAS Visual Analytics.

Explore data and create or adjust predictive analytics models with this solution running in SAS and Viya.

 Data scientists, statisticians, and analysts can collaborate for each department or group to make decisions based on accurate insights and iteratively refine models.

SAS Enterprise Miner

Streamline the data mining process and create predictive and descriptive models based on analytics. SAS Enterprise Miner helps you analyze complex data, discover patterns, and build models so you can more easily detect fraud, anticipate resource demands, and minimize customer attrition.

Organizations across a range of industries rely on data analytics to support new businesses in crucial product development decisions, foresee future risks, boost competition in new markets, and target new customers. Data analytics is used to examine existing data-based performance and identify various organizational inefficiencies.

In India, there is a sizable data analytics market, and the sector is expanding quickly because to digitization. The data analytics sector is predicted to produce 1 million employment by 2026, and investments in AI and machine learning will rise.

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