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    Defect Management & Qa Reporting: Metrics & Kpis

    Posted By: ELK1nG
    Defect Management & Qa Reporting: Metrics & Kpis

    Defect Management & Qa Reporting: Metrics & Kpis
    Published 5/2025
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.61 GB | Duration: 4h 49m

    Learn defect lifecycle, bug tracking, Quality Assurance (QA) & Quality Control (QC) KPIs, metrics analysis, & reporting

    What you'll learn

    Selecting the right QA metrics for your project

    Interpreting trends in test result data

    Aligning QA metrics with business objectives

    Detecting quality issues early using metrics

    Integrating metrics into sprint planning

    Using KPIs to support go/no-go decisions

    Setting metric-based quality gates

    Using data to justify QA resource needs

    Visualizing test progress over time

    Monitoring automation stability with key indicators

    Analyzing root causes of recurring defects

    Supporting team retrospectives with hard QA data

    Driving test strategy with measurable outcomes

    Requirements

    General knowledge of software testing principles

    Understanding of QA workflows, whether manual or automated

    Prior use of bug tracking systems like Jira or similar

    Experience working with test management platforms such as TestRail or Zephyr

    A desire to improve QA through data and metrics

    No need for deep coding or statistical skills

    Description

    Master Defect Management, QA Reporting & KPIs – Elevate Your Software Quality with Actionable Metrics & KPIsWant to gain full control over your QA process and confidently communicate software quality to stakeholders? This course is your complete guide to defect management, QA reporting, and quality metrics — designed to help you lead your QA efforts with data, not guesswork."Defect Management & QA Reporting: Metrics & KPIs" is a hands-on, practical course that shows you how to track, analyze, and improve your QA process using industry-proven metrics and reporting practices. From managing the defect lifecycle to building KPI-driven dashboards, you’ll learn how to drive results in both Agile and traditional environments.What You Will LearnThe complete defect lifecycle from detection to closure (and everything in between)Key QA and QC KPIs: defect density, leakage rate, test coverage, test execution status, MTTR, and moreHow to build effective QA dashboards and reporting frameworks for stakeholdersTechniques for root cause analysis, defect triage, and severity-priority alignmentStrategies to avoid common pitfalls in bug tracking and status reportingAligning QA metrics with business goals to show ROI of testing effortsThis course gives you not just theory—but practical templates, real-world examples, and step-by-step demonstrations to apply what you learn right away.Who This Course is ForQA Engineers and Manual Testers who want to bring clarity and structure to their defect trackingAutomation Engineers seeking to integrate defect and test metrics into CI/CD pipelinesQA Leads and Managers looking to improve visibility, traceability, and reporting practicesScrum Masters and Agile Teams who need reliable quality insights per sprint or releaseBusiness Analysts and Product Managers interested in understanding and interpreting quality reportsWhat Makes This Course DifferentMost QA courses focus only on test execution. This one gives you the data-driven backbone of QA work — metrics, reporting, and quality control. You’ll learn how to turn bugs into valuable insights, how to build trust with stakeholders using data, and how to level up your QA career through analytics and visibility.By the end of this course, you'll be able to track defects with confidence, build reports that influence decisions, and measure QA success with the right KPIs.Sign up now and transform your QA efforts into a measurable, strategic force for software quality.

    Overview

    Section 1: Introduction

    Lecture 1 Communication plan

    Lecture 2 Tips to Improve Your Course Taking Experience

    Section 2: Defect Management Metrics & KPIs

    Lecture 3 Defect Management Metrics & KPIs: Number of Open Defects & Defect Leakage

    Lecture 4 Defect Management Metrics & KPIs: Defects per Severity/Priority/Env/Root cause

    Lecture 5 Defect Management Metrics & KPIs: Defect Density, Non-Resolved Blockers & Others

    Lecture 6 Defect Management Metrics & KPIs: Quality Debt Index, Bug Fixing Projection

    Lecture 7 Defect Reopen, Defect Rejection, Open Defects Change Rate, Removal Efficiency

    Lecture 8 Defect Resolution Time, Defect Age, Detection to Resolution Ratio

    Section 3: Testing Metrics & KPIs

    Lecture 9 Test execution coverage, Cost of Quality & Test Design Coverage

    Lecture 10 Testing Metrics & KPIs: Regression Time, Verified Issues Rate, Pass Rate

    Section 4: Test Automation Metrics & KPIs

    Lecture 11 % of Poduct, Automation, System Issues & Execution Frequency

    Lecture 12 Execution Time, Test Success Ratio & % of Results Analyzed

    Lecture 13 Regression Effectiveness, Percentage of Automated Tests & Auto Savings

    Section 5: Bonus Section

    Lecture 14 Bonus Lesson

    Manual testers looking to validate their contributions using measurable outcomes,Automation specialists aiming to prove the effectiveness and stability of their frameworks,QA leaders and coordinators seeking to build data-driven quality processes,Agile quality professionals working to synchronize testing with rapid development cycles,Business analysts and product owners wanting a clearer view of product health through QA metrics,Developers interested in leveraging QA insights to improve code quality and reduce defects,Project leaders who need to oversee quality levels and manage risks effectively,Delivery heads focused on ensuring release quality and identifying potential blockers,Engineering leaders aiming to track and enhance team output using quality indicators,Product strategists wanting to connect quality data to product planning and outcomes,Architects who want to analyze how design choices impact defects and system stability