Data quality is not a filter, it's a discipline

Description:
Every vendor says their data is clean, but can they prove it? Data quality is a business issue that affects stakeholder trust and decision speed. The hosts introduce a framework to help researchers move from simply filtering out bad data to building a discipline of quality.

You’ll learn:
- The costs of poor data quality
- Why standard filters miss the majority of fraud
- The four P framework for data integrity
- How to vet vendors for sophisticated threats like AI responses
- Why transparency is the new standard for the industry

Chapters:
[00:02:48] The costs of bad data
[00:05:48] Going from just filters to discipline
[00:08:46] How market dynamics drive change
[00:11:22] The four P framework: prevent, protect, purify, and prove
[00:13:00] Red flags in vendor evaluations
[00:17:04] Building a data quality framework
[00:20:54] Closing reflections

Episode Resources:
- Stephanie Vance on LinkedIn - https://tinyurl.com/55u35t49
- Molly Strawn-Carreño on LinkedIn - https://tinyurl.com/445492hz
- aytm on LinkedIn - https://tinyurl.com/z67trrje
- aytm Website - https://tinyurl.com/2d5a8uh4