Lesson 1: Understanding and Describing DataThe World of DataMethods of Descriptive StatisticsStatistical Significance Testing
The World of Data
Methods of Descriptive Statistics
Statistical Significance Testing
Lesson 2: The Basics of SQL for AnalyticsRelational Databases and SQLBasic Data Types of SQLReading Tables: The SELECT QueryCreating TablesUpdating TablesDeleting Data and TablesSQL and 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 PreparationAssembling DataTransforming Data
Assembling Data
Transforming Data
Lesson 4: Aggregate Functions for Data AnalysisAggregate FunctionsAggregate Functions with GROUP BYThe HAVING ClauseUsing Aggregates to Clean Data and Examine Data Quality
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 AnalysisWindow FunctionsStatistics with Window Functions
Window Functions
Statistics with Window Functions
Lesson 6: Importing and Exporting dataThe COPY CommandUsing R with Our DatabaseUsing Python with Our DatabaseBest Practices for 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 TypesDate and Time Data Types for AnalysisPerforming Geospatial Analysis in PostgresUsing Array Data Types in PostgresUsing JSON Data Types in PostgresText Analytics Using Postgres
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 SQLDatabase Scanning MethodsPerformant JoinsFunctions and Triggers
Database Scanning Methods
Performant Joins
Functions and Triggers
Lesson 9: Using SQL to Uncover the Truth - A Case StudyCase Study
Case Study

Learner Outcomes
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