Learn defect lifecycle, bug tracking, Quality Assurance (QA) & Quality Control (QC) KPIs, metrics analysis, & reporting
What you will 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
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- Master the entire lifecycle of software defects, from initial identification and logging through to verification and closure, ensuring a streamlined and effective bug management process.
- Develop proficiency in selecting and implementing robust bug tracking systems, understanding how to configure and leverage these tools for maximum efficiency and traceability.
- Gain a deep understanding of Quality Assurance (QA) and Quality Control (QC) Key Performance Indicators (KPIs), recognizing their strategic importance in assessing and improving product quality.
- Become adept at analyzing a wide range of QA metrics, transforming raw data into actionable insights that drive quality improvements and reduce technical debt.
- Learn to create compelling and informative QA reports that clearly communicate quality status, risks, and trends to stakeholders at all levels.
- Understand the principles of defect prevention by leveraging metric analysis to identify systemic issues and implement proactive quality measures.
- Explore the role of metrics in optimizing testing strategies, ensuring that testing efforts are focused, efficient, and aligned with project goals.
- Discover how to quantify the effectiveness of testing activities and demonstrate the value of QA to the business through data-driven reporting.
- Learn to identify and interpret patterns in test execution data to predict potential quality bottlenecks and proactively address them.
- Understand how to translate subjective quality perceptions into objective, measurable data, enabling more informed decision-making.
- Develop the ability to benchmark QA performance against industry standards and internal historical data to identify areas for continuous improvement.
- Learn to articulate the impact of defects on business objectives and customer satisfaction using relevant QA metrics and reporting.
- Explore techniques for forecasting future defect trends based on current project data and identified risk factors.
- Understand how to build a culture of quality within development teams by fostering data-driven discussions and feedback loops.
- Gain insights into reporting on the health of automated test suites and identifying factors affecting their reliability.
- PROS:
- Provides a foundational understanding of essential QA processes and their measurement.
- Equips participants with practical skills for data analysis and reporting in a QA context.
- Enhances ability to contribute to informed decision-making regarding software quality.
- CONS:
- May require prior exposure to software development methodologies for maximum benefit.
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