The logic for turning data into information must live somewhere, whether it’s in people’s heads or in an automated process. The goal of a Data Strategy is to gain consensus with the Executive sponsors and their constituents so that the organization can inject reusability into the data landscape. This ensures that every aspect of the data-to-information process is not an expensive and time-consuming bespoke event.
But how do you get there? How do you get this consensus with so many competing interests? In this session, SqlDBM and Intricity step through the ground zero assets that build the consensus needed for automation in a data model.
In this session you will learn about:
- Obtaining architectural consensus
- Planning budgets for Executive Sponsorship
- Assets to gain topical consensus across business lines
- Leveraging assembled assets to generate collaborative data models
- Iteration of conceptual models to harden data models
