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SQL for Data Analytics

(SQL-DA.AJ1)/ISBN:978-1-64459-222-9

This course includes
Lessons
TestPrep
Hand-on Lab
AI Tutor (Add-on)
SQL for Data Analytics

Gain hands-on expertise to work with SQL for Data science with the SQL for Data Analytics course and lab. Lab simulates real-world, hardware, software, and command-line interface environments and can be mapped to any textbook, course, or training. The SQL course and lab will teach everything from the basics of SQL for Analytics to SQL for Data preparation, aggregate functions for Data analysis, importing and exporting data; analytics using complex data types, and more.

Lessons

10+ Lessons | 60+ Quizzes | 40+ Flashcards | 40+ Glossary of terms

TestPrep

55+ Pre Assessment Questions | 55+ Post Assessment Questions |

Hand on lab

37+ LiveLab | 00+ Minutes

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Here's what you will learn

Download Course Outline

Lessons 1: Understanding and Describing Data

  • Introduction
  • The World of Data
  • Methods of Descriptive Statistics
  • Statistical Significance Testing
  • Summary

Lessons 2: The Basics of SQL for Analytics

  • Introduction
  • 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
  • Summary

Lessons 3: SQL for Data Preparation

  • Introduction
  • Assembling Data
  • Transforming Data
  • Summary

Lessons 4: Aggregate Functions for Data Analysis

  • Introduction
  • Aggregate Functions
  • Aggregate Functions with GROUP BY
  • The HAVING Clause
  • Using Aggregates to Clean Data and Examine Data Quality
  • Summary

Lessons 5: Window Functions for Data Analysis

  • Introduction
  • Window Functions
  • Statistics with Window Functions
  • Summary

Lessons 6: Importing and Exporting Data

  • Introduction
  • The COPY Command
  • Using R with Our Database
  • Using Python with Our Database
  • Best Practices for Importing and Exporting Data
  • Summary

Lessons 7: Analytics Using Complex Data Types

  • Introduction
  • 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
  • Summary

Lessons 8: Performant SQL

  • Introduction
  • Database Scanning Methods
  • Performant Joins
  • Functions and Triggers
  • Summary

Lessons 9: Using SQL to Uncover the Truth – a Case Study

  • Introduction
  • Case Study
  • Summary

Appendix

  • Installing pgAdmin 4

Hands-on LAB Activities

Understanding and Describing Data

  • Sandbox

The Basics of SQL for Analytics

  • Using the ORDER BY Clause
  • Using the SELECT Statement
  • Using the WHERE Clause
  • Using the AND Clause
  • Using the NOT IN Clause
  • Using the LIMIT Clause
  • Using the CREATE TABLE Statement
  • Using the INSERT INTO…VALUES Statement
  • Using the UPDATE Statement
  • Adding a Column to a Table
  • Using the DROP TABLE Statement
  • Using the DELETE Statement

SQL for Data Preparation

  • Using the Cross Join
  • Using the Inner Join
  • Using the Left Outer Join
  • Using the Right Outer Join
  • Using the DISTINCT Keyword
  • Using the CASE WHEN Statement

Aggregate Functions for Data Analysis

  • Using the AVG Function
  • Using the COUNT Function
  • Using the GROUP BY Clause
  • Using the HAVING Clause

Window Functions for Data Analysis

  • Using the PARTITION BY Clause

Importing and Exporting Data

  • Using the COPY Command

Analytics Using Complex Data Types

  • Using the INTERVAL Keyword
  • Using the EXTRACT Keyword
  • Using the now() Function
  • Understanding the current date Keyword
  • Using the STRING_TO_ARRAY Function
  • Using the REGEXP_REPLACE Function
  • Using the row_to_json Function
  • Using the ARRAY_TO_STRING Function

Performant SQL

  • Using the DROP INDEX Command
  • Using the CREATE INDEX Command
  • Using the EXPLAIN Command
  • Creating an Index on a Column of a Table of a Database