Structured Query Language (SQL) is an indispensable skill in the data science industry and generally speaking, learning this skill is relatively straightforward. However, most forget that SQL isn’t just about writing queries, which is just the first step down the road. Ensuring that queries are performant or that they fit the context that you’re working in is a whole other thing.
Why should you learn SQL for data science?
SQL is one of the most in-demand skills that you find in job descriptions from the data science industry, whether you’re applying for a data analyst, a data engineer, a data scientist or any other roles. This is confirmed by 70% of the respondents of the 2016 O’Reilly Data Science Salary Survey, who indicate that they use SQL in their professional context. What’s more, in this survey, SQL stands out way above the R (57%) and Python (54%) programming languages. SQL is a must-have skill when you’re working towards getting a job in the data science industry.
But why exactly is it that it is so frequently used? And why isn’t it dead even though it has been around for such a long time? There are several reasons: one of the first reasons would be that companies mostly store data in Relational Database Management Systems (RDBMS) or in Relational Data Stream Management Systems (RDSMS) and you need SQL to access that data. SQL is the lingua franca of data: it gives you the ability to interact with almost any database or even to build your own locally!
As if this wasn’t enough yet, keep in mind that there are quite a few SQL implementations that are incompatible between vendors and do not necessarily follow standards. Knowing the standard SQL is thus a requirement for you to find your way around in the (data science) industry. On top of that, it’s safe to say that SQL has also been embraced by newer technologies, such as Hive, an SQL-like query language interface to query and manage large datasets, or Spark SQL, which you can use to execute SQL queries. Once again, the SQL that you find there will differ from the standard that you might have learned, but the learning curve will be considerably easier.
Learn more about querying databases in the HURU School Data Science Course