Topics for this video,

1. Show how data analytics team is using Microsoft teams task planner for task assignment
2. Data validation in Power BI against the benchmark numbers provided by the product owner
3. Address gaps found during data validation

In the video, for Total forecast Qty you will see a gap of 376 K which I ask a data engineer to fix it and eventually it matches the correct number which is 86.82436M for the year 2022. When you practice this, you will not see any gap because the dataset that is provided to you has this issue fixed already. So do not worry if your numbers are matching without any gap. The idea here is to show data quality issues that come up in organizations and how they take care of fixing them.