Online Course
Customer Churn Analysis with SQL and Tableau

Gain first-hand data analyst experience: Use SQL and Tableau to tackle real-world business challenges

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  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Skill level:

Intermediate

Duration:

3 hours
  • Lessons (3 hours)
  • Practice exams (20 minutes)

CPE credits:

4.5
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org

Accredited:

certificate

What You Learn

  • Improve your SQL and Tableau proficiency by tackling real-world business data.
  • Perform churn analysis for a SaaS business and uncover revenue insights.
  • Create professional multi-page Tableau dashboards with polished formatting.
  • Identify customer churn metrics, lifetime value, and revenue breakdowns.
  • Add a unique project to your portfolio with professional data visualizations.

Topics & tools

tableaudashboardmysql querybar chartdata visualizationcustomer churndata analysisorder frequency tablebubble chartcohort analysis tableline chartmapsSQLdashboard reportingbusiness skills

Your instructor

Course OVERVIEW

Description

CPE Credits: 4.5 Field of Study: Specialized Knowledge
Delivery Method: QAS Self Study
Analyzing customer behavior based on data is becoming necessary for any business to understand its consumer base. In this course, you’ll learn how to define and analyze customer churn metrics, such as customer retention rate, customer re-subscription rate, customer lifetime value, and more. We’ll work with a real database, query it using MySQL, and create a Tableau dashboard based on the customer data. You’ll learn how to create maps and cohort tables, use Tableau filters, and more.

Prerequisites

  • Any SQL environment (such as SQLite, MySQL Workbench, or an online SQL editor).
  • Tableau Desktop or Tableau Public
  • Python (version 3.8 or later), pandas library, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code)

Advanced preparation

Curriculum

39 lessons 4 exercises 2 exams

Free preview

Introduction to the course

1.1 Introduction to the course

5 min

Motivation - Our Story

2.1 Motivation - Our Story

5 min

Intro to the business case

2.2 Intro to the business case

3 min

Basic Terminology - Net Revenue, Refunds, New vs Recurring Revenue

2.3 Basic Terminology - Net Revenue, Refunds, New vs Recurring Revenue

3 min

Types of customers

2.4 Types of customers

4 min

Basic Terminology - Customer Churn and Customer Retention

2.5 Basic Terminology - Customer Churn and Customer Retention

7 min

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ACCREDITED certificates

Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global institutions.

Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities employers value most.

  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Certificates are included with the Self-Study learning plan.

A LinkedIn profile mockup on a mobile screen showing Parker Maxwell, a Certified Data Analyst, with credentials from 365 Data Science listed under Licenses & Certification. A 365 Data Science Certificate of Achievement awarded to Parker Maxwell for completing the Data Analyst career track, featuring accreditation badges and a gold “Verified Certificate” seal.

How it WORKS

  • Lessons
  • Exercises
  • Projects
  • Practice Exams
  • AI Mock Interviews

Lessons

Learn through short, simple lessons—no prior experience in AI or data science needed.

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Exercises

Reinforce your learning with mini recaps, hands-on coding, flashcards, fill-in-the-blank activities, and other engaging exercises.

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Projects

Tackle real-world AI and data science projects—just like those faced by industry professionals every day.

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Practice Exams

Track your progress and solidify your knowledge with regular practice exams.

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AI Mock Interviews

Prep for interviews with real-world tasks, popular questions, and real-time feedback.

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Student REVIEWS

A collage of student testimonials from 365 Data Science learners, featuring profile photos, names, job titles, and quotes or video play icons, showcasing diverse backgrounds and successful career transitions into AI and data science roles.