Topic – Data Analysis and Visualization: Upskilling Testers for Smarter Data Testing

As data complexity grows, testers need to upskill with Data Analysis and Visualization techniques to stay ahead. This interactive session focuses on empowering testers with practical skills using Python and Excel to enhance their data testing capabilities.

Participants will:

• Learn key data analysis techniques, such as anomaly detection, trend analysis, and data cleansing, using Python libraries (pandas, matplotlib, seaborn) and Excel’s advanced features (Power Query, PivotTables, and Conditional Formatting).
• Explore real-world examples, including validating data pipelines, detecting inconsistencies, and ensuring data accuracy for AI systems and Big Data projects.
• Apply these techniques in hands-on exercises, such as visualizing test results, creating trend dashboards, and identifying data anomalies.

By the end of this session, attendees will:

1. Understand how to leverage Python and Excel for efficient and scalable data testing.
2. Be equipped to analyze and visualize data to uncover hidden patterns and ensure quality.
3. Gain actionable insights to improve reporting and communication with stakeholders.

Join us to discover how mastering Python and Excel can elevate your testing craft and future-proof your skills in a data-driven world!