Lately, I'm noticing a lot of SQL Server community questions, confusion, concerns, and even surprising hostility around the term analytics. Without a doubt, analytics is popular throughout the entire data ecosystem and wider technology industry outside of the SQL Server world right now. Microsoft didn't invent or make-up the term analytics as data comedians in our community suggested in social networks. Look around you. Across the data world, all of the major vendors in our space are using this "hot" keyword today. It's time to embrace the inevitable analytics market evolution or be left behind.
How Analytics Relates to SQL Server
I recently wrote about trends and the longer term, ongoing market shift from business intelligence towards business analytics in Business Intelligence Market Shifts. In the article, I shared that analytics is more of a forward looking approach using data to gain business insights. Analytics means interacting with information at the speed of business, continuous iterative data discovery, exploration, and fact-based decision making using statistical and quantitative analysis, explanatory, predictive, and prescriptive modeling. I also compared analytics to the traditional business intelligence (BI) activities that we already know and embrace. What I didn’t specifically spell out in that article was how analytics relates to SQL Server. I assumed it was obvious. After seeing quite a bit of heated chatter on this topic, I'm now thinking that the connection between SQL Server and analytics is not easy for everyone to see. Let me take this opportunity to connect and clarify a few of these concepts.
Analytics is Not Synonymous with Excel
Does analytics mean Excel users? First of all, NO, analytics is not synonymous with Excel. In my mind, analytics is a broad term with varied interpretations. Analytics often includes Excel as an analytical tool, but there are also quite a few other tools including analytical functionalities within SQL Server. I personally like the definition and structure that INFORMS presents for analytics.
Descriptive Analytics
- Prepares and analyzes historical data
- Identifies patterns from samples for reporting of trends
Predictive Analytics
- Predicts future probabilities and trends
- Finds relationships in data that may not be readily apparent with descriptive analysis
Prescriptive Analytics
- Evaluates and determines new ways to operate
- Targets business objectives
- Balances all constraints
If I take these categories and relate them to SQL Server world, you might be able to relate to analytics a little bit better. Although this list is not complete by any means, I'm going to guess that you'll recognize and probably have even used a few of these tools in your past SQL Server related projects.
Descriptive Analytics |
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Predictive Analytics |
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Prescriptive Analytics |
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For Further Learning
There are many resources for ramping up on analytics. Coursera and Microsoft Virtual Academy (MVA) free courses include beginning through advanced analytics topics. In future SQL Server Pro articles, we'll dive into different areas of analytics with real-world examples and explanations on when to choose one analytical problem-solving technique over another. By this time next year, I'm hoping that many more folks in our SQL Server community will warmly welcome the analytics shift. It should be enjoyable getting cozy with the meaning of the data that we have been storing and querying throughout our entire careers.
