MAD Data: An ML, AI, and Data Podcast by Databand

31 Episodio

1. The Impacts Of Generative AI For Data Integration

   Pubblicato: 8/6/2023
2. All Things Airflow: Past, Present And Future

   Pubblicato: 23/3/2023
3. Data Quality Through The Lens Of An Analytics Engineer

   Pubblicato: 24/2/2023
4. The Future Of Data Fabric And Data Integration

   Pubblicato: 7/12/2022
5. How To Reduce Data System Complexities

   Pubblicato: 9/11/2022
6. How Incident Management Supplements Data Governance

   Pubblicato: 17/10/2022
7. How Engineering Can Deliver Better Value For Data Science

   Pubblicato: 16/9/2022
8. Lessons Learned Building World-Class Data Engineering Teams

   Pubblicato: 11/8/2022
9. The Case for Dataset Centric Visualization

   Pubblicato: 27/7/2022
10. Unveiling The IBM Acquisition Of Databand

    Pubblicato: 20/7/2022
11. Two Philadelphians Talk Data Startups And Building An Analytics Community

    Pubblicato: 22/6/2022
12. How Warby Parker Builds Repeatable Data Engineering Playbooks

    Pubblicato: 10/6/2022
13. How Pinterest Is Migrating To The Modern Data Cloud With Confidence

    Pubblicato: 25/5/2022
14. How To Avoid The Vortex Of Data Debt

    Pubblicato: 11/5/2022
15. How To Treat Data As A Product

    Pubblicato: 27/4/2022
16. Lights On Your Dark Data Quality Issues

    Pubblicato: 13/4/2022
17. Clean Data At The Source: When & Why This Matters To Your Business

    Pubblicato: 28/3/2022
18. Next Gen Data Demands: Real-Time Alerting & Complex Data Ingestion

    Pubblicato: 17/3/2022
19. The Case For Data Catalogs: Are Your Teams On The Same Page?

    Pubblicato: 23/2/2022
20. Where Should Data Quality Sit? It Depends.

    Pubblicato: 9/2/2022