There are many opinions on data in regards to its impact on an infrastructure or organization. One opinion that resonates in my head specifically and that I have heard time and time again is "Data only gets worse, not better." While this may be true to an infrastructure point of view, what about another perspective? Opportunity. So much time is spent on data integrity and infrastructure that sometimes that overshadows what data truly means for you and your business. Let's take a look at that different perspective.
So what actually is R?
R presents one of those opportunities with data. R is a language and an environment that was derived from S or “Statistics” Language from the 1970’s. Its sole purpose is to provide a data analytics solution. R is also not just a language. R “has” a language in a sense. We are also not creating database objects with R. R is not a database platform or for managing data like you would in SQL Server. It is also not a data warehouse or a warehousing framework or methodology. It is not “Business Intelligence” but rather a tool of Business Intelligence. R is analysis only. R USES data from your data storage and infrastructure services. R is a tool to help consume data by your business units who actually need to understand the data and so they can make strategic decisions based off of the data.
Why R then? What’s so wrong with SSAS?
In a word, nothing. However, they’re also not one in the same either. With SSAS, you’re creating schemas, cubes, and using an application such as Excel to consume that data. R has its own unique service for SQL Server 2016, creatively called “SQL Server R Services.” It provides the capability to create rich, easy to use, and detailed models in both reporting and visual charts and graphs, something that SQL cannot do without additional tools. R does this by harnessing flexibility as a language that is rather intuitive to understand in the way it handles objects, vectors, and the syntax of the language. Not everyone can understand a SQL query, however it is relatively easy to understand N <- 1 + 3. ‘N’ probably equals 4, doesn’t it? What if you wanted to have a single cell in SQL set to 4? You would have to declare the variable, set the variable, then output the variable. Oh and now that we have set the variable, if we want to set that variable to something else, we would have to recode the query. In R, you can simply rescript that variable to the new value. R also isn’t just scripting. You can also call the R script in a SQL query for reusability and flexibility. The opportunities are vast when combining R with SQL.
As we continue our journey through the world of Business Intelligence using R, I will reveal more content that can show you how to unleash the capabilities of R, SQL Server R Services, and SQL Server 2016.