Mastering Software Quality: A Data-Driven QA & QC Approach

What you will learn:

Analyze test execution progress with key metrics
Extract actionable insights from defect trends
Identify and eliminate QA process inefficiencies
Measure defect escape rate to production
Detect gaps in test scenarios using metrics
Estimate ROI from automation testing
Implement metric-driven test planning
Integrate manual and automated testing metrics
Track QA team productivity over time
Define project-specific QA & QC KPIs
Use metrics to support compliance and audits
Evaluate project quality levels using metrics
Quantify the cost of poor quality (CoPQ)
Establish metric-based QA OKRs
Use metrics to facilitate root cause analysis
Differentiate bug severity and priority for effective triage
Communicate QA results effectively via reports
Use data in retrospectives to improve QA strategies
Identify and define key QA indicators and metrics
Evaluate system test coverage and effectiveness

Description

Transform your QA process with data-driven insights! This comprehensive course empowers QA engineers, testers, and managers to leverage key metrics and KPIs for enhanced software quality and efficient team performance.

Learn to measure, improve, and communicate software quality effectively using practical, real-world examples. Master the art of defect analysis, automation effectiveness, and quality measurement strategies. This course goes beyond theory, providing you with actionable tools, templates, and dashboards (Jira, Excel, TestRail) to immediately improve your workflow.

Here's what you'll gain:

A deep understanding of core QA & QC metrics and KPIs, and the crucial distinction between them.
Proven techniques for analyzing defect trends, pinpointing root causes, and mitigating risks.
Effective strategies for measuring the success of both manual and automated testing efforts—execution rates, pass/fail ratios, automation coverage, and more.
Practical frameworks for tracking test coverage, product readiness, and test case effectiveness.
Data-driven approaches to optimizing test cycles, reducing technical debt, and driving process improvements in Agile and DevOps environments.
Master the art of building compelling visual reports and dashboards using popular tools like Jira, Excel, or TestRail.

Whether you're a seasoned QA professional or just starting out, this course provides the knowledge and tools to build a robust, metric-driven QA practice that delivers demonstrable results. Stop guessing—start measuring! Enroll today and unlock the power of data in QA.

Curriculum

Introduction

This introductory section sets the stage for the course, covering essential communication strategies in a QA context and providing valuable tips to optimize your learning experience. The lectures on 'Communication Plan' and 'Tips to Improve Your Course Taking Experience' lay a solid foundation for your journey toward mastering data-driven QA.

Defect Management Metrics & KPIs

Dive deep into the core metrics that illuminate the health of your software. Lectures cover a range of key indicators including open defects, defect leakage, defects per severity/priority/environment/root cause, defect density, unresolved blockers, quality debt index, bug fixing projection, defect reopen rate, rejection rate, open defects change rate, removal efficiency, defect resolution time, defect age, and detection-to-resolution ratio. You will gain the ability to analyze and interpret these metrics to proactively address issues and improve overall quality.

Testing Metrics & KPIs

This section expands on the overall testing process. Learn how to effectively measure and analyze test execution coverage, cost of quality, test design coverage, regression time, verified issues rate, and pass rate. By mastering these metrics, you will have a clear understanding of your testing efficiency and effectiveness.

Test Automation Metrics & KPIs

Focuses specifically on the performance and efficiency of your automation efforts. Covering metrics such as percentage of product, automation, and system issues, execution frequency, execution time, test success ratio, percentage of results analyzed, regression effectiveness, percentage of automated tests, and automation cost savings, this section will help you justify and optimize your automation investments.

Bonus Section

This section provides extra information and resources to help you consolidate your knowledge and apply your skills effectively.

Deal Source: real.discount