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Data Analysis

Advanced Game Analysis With SQL

Building on the Game Analysis With SQL course, this course includes SQL techniques such as sub-queries, temporary tables, window functions and query optimization.

4 Weeks
16 hrs Of Instruction


Next Course:     
September 2024

What You'll Learn

Window Functions: How window functions can simplify complex game data analysis. Window function FRAMEs, PARTITIONs and ORDERing. RANKing and percentile functions. Rolling averages, cumulative sum and improve game analysis efficiency and insight.

Jupyter Notebooks: How to install and use Jupyter, a web-based notebook for analytics. How to use Jupyter to analyze data using SQL and Python. How to use Python libraries for game analysis. Common Python libraries for statistics, visualization, machine learning and more. 

Advanced Game Analysis: Using SQL to analyze game economies. Understanding game network health. Using SQL to monitor game inflows and outflows. Advanced monetization analysis and pricing. How to determine economy balance. How to use SQL for cohort analysis and LTV prediction. 

Predictive Models & Dashboards: SQL techniques for preparing data for dashboards, reports and predictive models. Examples of churn and payer prediction using SQL. Combining SQL extraction, data and Python libraries to forecast player behavior. 

Common Table Expressions (CTEs): How to use CTEs. The purpose of CTEs and code maintainability. Reducing queries complexity and improving analysis throughout. Recursive queries and when to use CTEs, sub-queries and temporary tables.

Query Optimization: The best way to run queries against large datasets. The impact of indexes. Which index type is best suited to which data. The EXPLAIN function and  query performance. How to sample with SQL and increase query throughput. 

Player Segmentation: How we can use SQL to discover player segments. Advanced analysis techniques using SQL and Python for K-Means clustering and decision trees.  Using SQL and Python for visualization and model development. 

Capstone Project: Capstone project requirements. Capstone project template and recommended approach. How to utilize assignments and course work for your capstone project.

Success strategies

Advanced Game Analysis With SQL

Building on the Game Analysis With SQL course, this course includes SQL techniques such as sub-queries, temporary tables, window functions and query optimization.

4 Weeks
16 hrs Of Instruction

Next Course:

September 2024

This Course Includes

  • Office Hours With Instructor, Schedulable Instructor 1-On-1s

  • 16 Hours of Instruction Delivered Over 8 Lessons

  • Downloadable Lesson Slides, Downloadable SQL and Python code

  • Lesson Assignments, Lesson Quizzes, In-Class Exercises

  • Final Course Quiz, Capstone Project For Analytics Portfolio

  • Certificate Of Completion, Digital Certificate Credentials

Course Content

LESSON 01: Window Functions - Part I

  • Introduction To Window Functions

  • Partitions, Frames, Bounds & Orders


  • ROW_NUMBER & RANK Functions

  • Cumulative Totals & Percentiles

  • Game Analytics Examples

  • Lesson Assignment & Quiz

LESSON 05: Query Efficiency

  • Indexes & Optimization

  • The Query Execution Plan

  • The EXPLAIN Function

  • Estimating Query Performance

  • Efficient Querying Using Sampling

  • Query Performance Best Practices

  • Lesson Quiz & Assignment

LESSON 02: Window Functions - Part II

  • MEDIAN, MODE & NTILES Functions


  • LEAD & LAG Functions

  • Rolling Averages

  • Window Aliases

  • Examples In Gaming

  • Lesson Assignment & Quiz

LESSON 06: Jupyter Notebook & Python Integration

  • Installing Jupyter Notebooks

  • Access To MySQL Database

  • Python Libraries For Data Analysis

  • SQL Workshop: Gaming Analysis With Python

  • Lesson Assignment & Quiz

LESSON 03: Sub-Queries & Temporary Tables

  • Sub-Queries Introduction

  • Temporary Tables Introduction

  • Self-Join, INTERSECT & IN

  • Performance Considerations

  • Examples In Gaming

  • Lesson Assignment & Quiz

LESSON 07: Advanced Analysis Workshop - Part I

  • Combining Metrics For Dashboards

  • Preparing Data For Model Development

  • SQL Workshop: Economy Analysis

  • SQL Workshop: Segmenting Players By Engagement & Monetization

  • Capstone Project - Part I

  • Lesson Assignment & Quiz

LESSON 04: Common Table Expressions

  • CTE Introduction

  • Combining Multiple Tables

  • Recursive Queries

  • Examples In Gaming

  • SubQueries vs Temporary vs CTE

  • Lesson Assignment & Quiz

LESSON 08: Advanced Analysis Workshop - Part II

  • SQL Workshop: Churn Model Development

  • SQL Workshop: Payer Prediction Model 

  • Capstone Project - Part II

  • Final Course Quiz


  • As an advanced course, we recommend learners complete the Game Analysis With SQL course first before taking this course, or have some previous experience in data analysis using SQL.

  • Learners can benefit from the Masterclass: Game Analysis With SQL course, which includes both the Game Analysis With SQL and Advanced Game Analysis With SQL course as a bundled discount.

  • Learners will need to be able to install MySQL, DBeaver, Python and Jupyter Notebook software on their Windows or Mac PCs to access and use the course data and code.


This course is a natural progression from the Game Analysis With SQL course. If you are new to SQL, we recommend taking the Game Analytics With SQL course first or the Masterclass: Game Analysis With SQL, which features both SQL courses with a bundle discount. 

Building on top of the Game Analytics With SQL course, this course brings several practical and hands-on workshops for advanced SQL analysis techniques used widely in gaming. In this course, learners will have the opportunity to install and use a MySQL database with game data and Jupyter Notebooks for analysis using SQL with supplied Python code.

Learners will understand and use advanced SQL analysis techniques such as window functions and common table expressions and how these are applied in gaming to understand economies, segment players and prepare data for dashboards, reports and use them in predictive model building. 

Finally, learners will understand how queries are executed and how to use database tools and SQL techniques to improve query efficiency and throughput using indexes, sampling and other advanced SQL constructs. 

This course features several assignments and quizzes to ensure that learners develop a full understanding of the course materials, are able to complete their capstone project and are eligible for a course completion certificate with distinction.

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