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

31 Episodo

1. The Impacts Of Generative AI For Data Integration

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    Publicado: 9/2/2022