SQL for Data Analytics

Take your first steps to become a fully qualified data analyst by learning how to explore large relational datasets.

Understanding and finding patterns in data has become one of the most important ways to improve business decisions. If you know the basics of SQL, but don’t know how to use it to gain business insights from data, this course is for you.


SQL for Data Analytics covers everything you need progress from simply knowing basic SQL to telling stories and identifying trends in data. You’ll be able to start exploring your data by identifying patterns and unlocking deeper insights. You’ll also gain experience working with different types of data in SQL, including time-series, geospatial, and text data. Finally, you’ll understand how to become productive with SQL with the help of profiling and automation to gain insights faster.

035465
3 days

By the end of the course, you’ll able to use SQL in everyday business scenarios efficiently and look at data with the critical eye of analytics professional.


After completing this course, you will be able to:

  • Use SQL to summarize and identify patterns in data
  • Apply special SQL clauses and functions to generate descriptive statistics
  • Use SQL queries and subqueries to prepare data for analysis
  • Perform advanced statistical calculations using the window function
  • Analyze special data types in SQL, including geospatial data and time data
  • Import and export data using a text file and PostgreSQL
  • Debug queries that won't run
  • Optimize queries to improve their performance for faster results
SQL for Data Analytics perfectly balances theory and practical exercises and provides a hands-on approach to analyzing data. It focuses on providing practical instruction in both SQL or statistical analysis so that you can better understand your data. The course takes away the crumbs and focuses on being practical. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.
If you’re a database engineer looking to transition into analytics, or a backend engineer who wants to develop a deeper understanding of production data, you will find this course useful. This course is also ideal for data scientists or business analysts who want to improve their data analytics skills using SQL. Knowledge of basic SQL and database concepts will aid in understanding the concepts covered in this course.
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  • OS: Windows 7, Mac OS X 10.8 or a recent GNU/Linux distribution
  • Browser: Google Chrome, Latest Version
  • VSCode IDE, Latest Version
  • Compiler: LLVM clang, Latest Version

For the optimal student experience, we recommend the following hardware configuration:

  • Processor: Intel Core i3 or equivalent
  • Memory: 2GB RAM
  • Storage: 1 GB available space processor: 2.5 GHz or higher (or equivalent)
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Lesson 1: Understanding and Describing Data

The World of Data

Methods of Descriptive Statistics

Statistical Significance Testing

Lesson 2: The Basics of SQL for Analytics

Relational Databases and SQL

Basic Data Types of SQL

Reading Tables: The SELECT Query

Creating Tables

Updating Tables

Deleting Data and Tables

SQL and Analytics

Lesson 3: SQL for Data Preparation

Assembling Data

Transforming Data

Lesson 4: Aggregate Functions for Data Analysis

Aggregate Functions

Aggregate Functions with GROUP BY

The HAVING Clause

Using Aggregates to Clean Data and Examine Data Quality

Lesson 5: Window Functions for Data Analysis

Window Functions

Statistics with Window Functions

Lesson 6: Importing and Exporting data

The COPY Command

Using R with Our Database

Using Python with Our Database

Best Practices for Importing and Exporting Data

Lesson 7: Analytics Using Complex Data Types

Date and Time Data Types for Analysis

Performing Geospatial Analysis in Postgres

Using Array Data Types in Postgres

Using JSON Data Types in Postgres

Text Analytics Using Postgres

Lesson 8: Performant SQL

Database Scanning Methods

Performant Joins

Functions and Triggers

Lesson 9: Using SQL to Uncover the Truth - A Case Study

Case Study

$216.00 USD

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