DataOps Is Good Business: Breaking Data Silos, Building Trust, and Preparing for AIErik Boemanns interviews Simon Yost on episode 14 of the E.B. Spoke podcast about DataOps as a practical operating model that, like DevOps, breaks down silos and turns analytics into a competitive advantage. They discuss how broken dashboards and surprise metrics become business costs when data is split across departments, and argue most companies have a data integration problem rather than a data problem. Examples include disconnects between marketing analytics and operational systems (even detecting website outages), and how unconnected data can mislead key metrics like customer lifetime value and acquisition costs. They emphasize tools don’t create trust—process, shared definitions (data dictionaries), and dedicated stewardship do—often via audits/gap assessments and a data fabric approach. They also cover Simon’s background, fractional consulting at the intersection of DataOps, data engineering, and AI, and the need to slow down to speed up while avoiding security/regulatory pitfalls.

00:00 Why Data Delays Hurt

00:24 DataOps Meets DevOps

00:50 From Firefighting to Flow

01:29 Invest in Data Foundations

02:09 One Off Spreadsheets Trap

02:50 Where Data Silos Form

03:36 Meet Simon Yost

04:56 Marketing vs Ops Disconnect

07:52 Lifecycle Pain and CLV

11:05 Unifying Data Patch to AI

12:25 Audits and the Brain Trust

13:48 Data Fabric Done Right

14:52 Warehouses Lakes Fabric

15:23 Open Source Data Stack

15:53 Data Dictionary Language

17:52 Owning Customer Definitions

19:11 Why Teams Can't Fix It

21:39 Slow Down To Speed Up

22:19 Regulation Changes Everything

24:41 AI Fear And Culture

26:16 Fractional Help And MVPs

27:59 From Prototype To Scale

29:23 Final Takeaway And Wrap