SQL for data science

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Of the 32,000 jobs on Indeed in early 2021 with data in the title, 43% wanted SQL skills. In 2017 the level of demand for SQL in data jobs was 36%. So even though SQL has been around since 1970 demand is increasing! Why is SQL for data science often a minimum requirement?

SQL is Everywhere

Uber, Netflix and Airbnb all use it. Facebook, Google and Amazon, who have their own high-performance database systems, use SQL for data science to query data and perform analysis. Facebook sorts a wide range of information for every user on SQL including user name, data of birth and any content they post.

If you query jobs on LinkedIn you will find more companies looking for SQL skills than for Python or R. On Indeed the title data analyst, the most common entry level job in the data scientist career track, requires SQL 57% of the time and is 1.5 times more common than Python and 2.5 times more commonly listed than R. Data Scientist job postings list SQL 58% of the time and for Data Engineers it is required in 56% of the job postings.

Data Scientist Vicknesh says, “SQL is so pervasive, it permeates everything here. It’s like the SQL syntax persists through time and space. Everything uses SQL or a derivative of SQL.”

But SQL is Old?!

In 1970, yes the 70’s, an IBM computer scientist, Edgar Codd, wrote a paper describing a new system for organizing data in databases. By the end of the 70’s several prototypes had been built and the Structured Query Language (correctly pronounced S.Q.L. or Sequel) began to interact with databases.

SQL is a fourth generation language which usually means it is far easier to understand and learn. It was the first language to allow access to multiple records with a single command, and it removed the need to specify how to reach a record in a database. Users could and can quickly and efficiently access data in a database and describe the data in a dataset. Users can manipulate the data and with the help of modules, libraries and pre-compilers SQL can be embedded within other languages. Most RDMA (Relational Database Management Systems) use SQL as their standard database language. This includes MySQL, MS Access, Oracle, Sybase, Informix, Postgres and SQL Server.

Yes, NOSQL and Hadoop were hot for a while but SQL remains the most popular language for data work. If you are a developer who works with data, more than 70% use SQL.

SQL for Data Science Courses

If you understand programming and already know some other languages you can learn SQL in a few weeks and then move on to more advanced skills like optimizing the database for speed. Beginners will be taught the basics like how to create a database, connect to a website and how to read/write data to the database. You must understand how and why a SQL database is used, be able to identify the key structures of a SQL database and get the information you need efficiently. These courses recommended by Medium.com should get you started with one included for the advanced leaner.

SQL for Data Science – This is Coursera’s best SQL for data science beginners. It teaches SQL fundamentals and how to work with data.

The Complete SQL Bootcamp – This is Udemy’s best SQL course because it starts from scratch and doesn’t require any previous programming skills or experience.

An Introductory Guide to SQL – Educative is an interactive coding and learning platform and this is their best SQL course. You will become familiar with one of the most popular and in-demand RDBMS – MySQL.

Complete SQL and Database Bootcamp: Zero to Mastery (2022) – This is real world experience working with all database types. You will be fully hands-on with many exercises offered to practice what you learn and test your knowledge. This course includes how machine learning, data science and data engineers use big data and databases.

High Performance SQL Course by Vlad Mihalcea – An advanced SQL course to master tough sQL and database concepts like lateral join, partitioning, Window functions and understanding execution plans. This course emphasizes writing high performance SQL for faster results.

Interested in talking about your career in data science? Contact Smith Hanley Associates’ Data Science and Analytics Executive Recruiter, Nancy Darian at ndarian@smithhanley.com.

 


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