SQL for Data Analytics

Course Duration: 3 days

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 to 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.

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

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.

 Target Audience

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.

Course Outline

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
Post Tagged with