# Analytics Data Quality - Overcoming Data Quality Challenges: Identifying Poor Data Sources and Setting Row Count Checks (Day 2 Lab)

> In these lab exercises, we address real-world data quality challenges by identifying poor data sources and establishing effective row count check thresholds.

- Web page: https://julie.techexpert.io/lesson/analytics-data-quality-day-2-lab-v2
- Program: [Data Engineering Boot Camp V2 Combined Track](https://julie.techexpert.io/program/data-engineering-boot-camp-v2-combined-track)
- Module: Week 5: Analytics Data Quality V2
- Access: Requires enrollment in Data Engineering Boot Camp V2 Combined Track
- Length: 50 min video
- Skills: SQL, Data Visualization, Statistics
- Academy: Julies academy to catch all other programs

## About this lesson

In these lab exercises, we address real-world data quality challenges by identifying poor data sources and establishing effective row count check thresholds.

## Navigation

- Previous lesson: [Analytics Data Quality - Mitigating Poor Data Quality: Causes, Contracts, and Row Count Thresholds (Day 2 Lecture)](https://julie.techexpert.io/lesson/analytics-data-quality-day-2-lecture-v2.md)
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