Ash Srivastava - October 8, 2024
Without high-quality data, even the most advanced analytics tools are ineffective.
Investing in data quality ensures that your insights are accurate, reliable, and actionable.
Conduct regular data profiling and cleansing activities to maintain data integrity.
What’s your biggest data quality challenge?
First shared on LinkedIn.
Dumping a database into a prompt doesn't solve search. In the AI era, data engineering is about filtering noise so the model gets the right context.
It was inspiring to share the stage with great leaders and engage with a room full of passionate professionals, students, and technology enthusiasts...
Documentation doesn't need to be a multi-month writing project. Record the work, let an LLM structure it, and review in thirty seconds.
Go deeper: AI Audit Checklist: What Auditors Will Ask For | NIST AI RMF Explained: Govern, Map, Measure, Manage
Weekly thinking on data and AI governance from Ash Srivastava.
