Part 12/13:

• Embedding controls: Use validation rules that can halt processing if issues are detected, avoiding compounding errors.

• Focus on reliability: Prioritize building systems that deliver consistent quality over time rather than just achieving initial quality snapshots.

By adopting this mindset, organizations can dramatically reduce failures, improve data trustworthiness, and maximize AI and analytics success.

Final Takeaway: Think Like a Factory for Data

Sesh concludes with a compelling analogy: "Would you fight a battlefield with a reliable weapon or just a good-quality one?" If reliability is paramount in high-stakes scenarios, then in data as well, prioritizing reliability over mere quality is essential.