Enhance Your QA Process with Metrics and KPIs

Enroll now in this Free Udemy Course to learn how to track QA metrics and improve software quality!

Delivering high-quality software in today’s competitive landscape means more than just ensuring functionality; it involves proving that quality through measurable data. This course, “QA Metrics & KPIs: Testing, Defect Tracking & Automation,” is designed for QA professionals eager to leverage data and key performance indicators to boost testing efficiency, minimize risk, and enhance overall software quality. Through a practical and in-depth approach, you will transform your testing methods into strategic assets that can be quantitatively analyzed and improved.

In this comprehensive course, you will explore crucial metrics such as test case pass rates, defect density, automation coverage, and more. Each module not only teaches you what metrics to track but also delves into why they are important, how to calculate them, and the optimal times to apply them. You’ll gain hands-on experience with your chosen defect tracking tools and learn to build effective reports and dashboards that communicate quality across teams, helping to align QA practices with business needs and agile methodologies.

Empower yourself to make informed decisions in your QA processes. By the end of this course, you’ll confidently define, collect, and report on the metrics that matter most for your projects. With practical tools, templates, and real-world examples, this workshop is not just theory; it’s a toolkit designed for immediate application, so you can start making your testing efforts visible, valuable, and truly impactful.

What you will learn:

  • How to define meaningful QA metrics and KPIs
  • Test case execution tracking and analysis
  • Measuring test coverage and test effectiveness
  • Calculating defect density and leakage rates
  • Understanding severity vs. priority in defects
  • How to assess test automation ROI
  • Tracking and reducing test flakiness
  • Using metrics in retrospectives and process reviews
  • Identifying and addressing QA bottlenecks
  • Metrics for evaluating sprint test readiness
  • Prioritizing tests with risk-based approaches
  • Leveraging defect trends to optimize coverage
  • Calculating mean time to detect and fix defects
  • Evaluating automation coverage and execution time

Course Content:

  • Sections: 5
  • Lectures: 15
  • Duration: 4h 51m

Requirements:

  • Basic understanding of software testing concepts
  • Familiarity with QA processes (manual or automated)
  • Experience with defect tracking tools (e.g., Jira, Bugzilla)
  • Some exposure to test case management tools (e.g., TestRail, Zephyr)
  • Interest in data-driven QA and continuous improvement
  • No advanced programming or statistics knowledge required.

Who is it for?

  • Manual testers wanting to show the value of their work with data
  • Automation test engineers needing to demonstrate ROI and reliability
  • QA leads and managers aiming to implement metric-driven processes
  • Agile QA professionals aligning testing with fast-paced delivery
  • Business analysts and product owners seeking insights into product quality through QA metrics
  • Software developers who want to understand QA impact and feedback loops
  • Project managers looking to track quality and delivery risk
  • Delivery managers focused on release readiness and defect trends
  • Engineering managers aiming to improve team performance through data
  • Product managers who need to align quality signals with product goals
  • Software architects interested in the relationship between system design and defect patterns.

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