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

31 Épisodes

1. The Impacts Of Generative AI For Data Integration

   Publié: 08/06/2023
2. All Things Airflow: Past, Present And Future

   Publié: 23/03/2023
3. Data Quality Through The Lens Of An Analytics Engineer

   Publié: 24/02/2023
4. The Future Of Data Fabric And Data Integration

   Publié: 07/12/2022
5. How To Reduce Data System Complexities

   Publié: 09/11/2022
6. How Incident Management Supplements Data Governance

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

   Publié: 16/09/2022
8. Lessons Learned Building World-Class Data Engineering Teams

   Publié: 11/08/2022
9. The Case for Dataset Centric Visualization

   Publié: 27/07/2022
10. Unveiling The IBM Acquisition Of Databand

    Publié: 20/07/2022
11. Two Philadelphians Talk Data Startups And Building An Analytics Community

    Publié: 22/06/2022
12. How Warby Parker Builds Repeatable Data Engineering Playbooks

    Publié: 10/06/2022
13. How Pinterest Is Migrating To The Modern Data Cloud With Confidence

    Publié: 25/05/2022
14. How To Avoid The Vortex Of Data Debt

    Publié: 11/05/2022
15. How To Treat Data As A Product

    Publié: 27/04/2022
16. Lights On Your Dark Data Quality Issues

    Publié: 13/04/2022
17. Clean Data At The Source: When & Why This Matters To Your Business

    Publié: 28/03/2022
18. Next Gen Data Demands: Real-Time Alerting & Complex Data Ingestion

    Publié: 17/03/2022
19. The Case For Data Catalogs: Are Your Teams On The Same Page?

    Publié: 23/02/2022
20. Where Should Data Quality Sit? It Depends.

    Publié: 09/02/2022