8 Resources For Data Scientists To Master SQL

SQL is considered one of the most favourable languages for database management.
SQL resources

SQL, or Structured Query Language, is domain-specific and was designed to manage data held in a relational database management system. As a part of the Query language, SQL was designed by Donald D, Chamberlin and Raymond F Boyce and first appeared in 1974. 

Developed with the goal of enabling non-programmers to excel at relational database management systems, SQL is regarded as a favourable language for database management and is supported by database systems like MySQL, SQL Server, and Oracle. Today, we list some resources (courses and books) that can help data scientists master SQL

If you are just beginning your SQL journey, read these tips to begin and this beginner’s guide first. 

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Master SQL: Udemy 

Delivered by instructor and software engineer Imtiaz Ahmad, this Udemy course on Master SQL for Data Science focuses on database basics, SQL Query Basics, using functions and subqueries, grouping data and computing aggregates, using CASE Clause, Window functions for analytics, working with multiple tables and advanced query techniques using correlated subqueries. 

On completing this course, one will be able to write complex SQL statements to query the database and gain critical insight into data. It is divided into 51 lectures across 11 sections and takes around 10 hours to complete. 

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Introduction to SQL: DataCamp

DataCamp’s Introduction to SQL is the first course under the SQL Fundamentals module. Through this hands-on course, one will be able to master the basics of querying tables in databases like MySQL, SQL Server and PostgreSQL. The instructor for this course is Nick Carchedi, Product Manager at DataCamp. The course focuses on the basics such as selecting columns, filtering rows, aggregating functions, sorting and grouping. The course usually takes up to four hours to complete. 

SQL for Data Science: Edx

Offered by Rav Ahuja, AI and Data Science Program Director at IBM, this introductory-level course– SQL for Data Science, will help one learn using and applying SQL to better communicate and extract detailed information from databases. This course covers the foundational knowledge of SQL, creating a database in the cloud, using string patterns and ranges to query data, analysing data using Python after sorting and grouping the results by type.  

This self-paced course is available for free and takes approximately four weeks to complete, provided one study for two to four hours every week. 

Advanced SQL for Data Scientists: LinkedIn Learning 

Offered by LinkedIn Learning, the Advanced SQL for Data Scientists course provides a sophisticated approach to optimising queries in SQL and designing data models. The course instructor is Enterprise Architect and Big Data expert Dan Sullivan and focuses on very large databases. The course is broadly divided into– data modelling: tables and indexes, query optimisation, user-defined functions and special-purpose functionality. 

On completion of this advanced course, which usually takes 2.5 hours to complete, students will receive a certificate.  


SQL for Smarties 

Joe Celko’s SQL for Smarties: Advanced SQL Programming is considered the first-ever book to be explicitly dedicated to introducing an SQL programmer to advanced techniques and mastering the programming language. The book does not just provide tips and techniques but also the best solutions to challenges one might encounter while trying to master SQL. 

SQL for Data Scientists: A Beginner’s Guide for Building Datasets for Analysis 

Written by Renee M Teate, SQL for Data Scientists: A Beginner’s Guide for Building Datasets for Analysis works as a stepping stone to SQL and dataset designing skills. The book focuses on constructing datasets for exploration, machine learning and analysis. On completion of this book, one will be well equipped to understand relational database structures, SQL syntax and query design; review approaches and strategies to help design analytical datasets, and develop queries to construct datasets that can be used for ML algorithms and interactive reports. 

SQL Cookbook: Query Solutions and Techniques for Database Developers

Written by expert SQL developer Anthony Molinaro, SQL Cookbook: Query Solutions and Techniques For Database Developers teaches about Window functions; features such as SQL Server’s PIVOT and UNPIVOT operators, PostgreSQL’s GENERATE_SERIES function, and Oracle’s MODEL clause; bucketization; creating histograms and the method of ‘walking a string.’ This book claims to help its readers take their SQL skills to the ‘next level.’

SQL Performance Explained 

Written by Markus Winand, SQL Performance Explained: Everything Developers Need To Know About SQL Performance, as the name suggests, covers all the major concepts and aspects of SQL databases without getting too focused on and lost in one single product. The book covers the usage of multi-column indexes, optimising join operations, using LIKE queries correctly, improving performance using clustering, and understanding the scalability of databases, among others. It covers all the major SQL databases such as Oracle Database, MySQL, SQL Server and PostgreSQL.  

Once you are familiar with the topic, here’s how you can crack SQL interviews

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