Delivering a Data Governance Program the Agile Way

The agile movement has taken over, and companies are switching their workforce away from traditional project and process management. Software development using Scrum is becoming an international norm. It is fast, fun, engaging, and satisfying. These terms typically are lacking when one describes implementing a data governance program. We've flipped the model and are applying the methodology on the business side. Attendees of this session will gain an understanding of how to grow a data governance program using Scrum, delivering value and assuring alignment for each and every sprint.

This data governance implementation success story will show how to break the end-state vision into unique building blocks (stories or Product Backlog Items), prioritize, and socialize with key stakeholders and quickly find value in the investment. Session attendees will be walked through an example sprint cycle, will see how the sprint events are applied to implementing data governance, and will better understand the value of artifacts created, most importantly the product backlog, or data governance program roadmap.

Events are key opportunities for communication, learning, and accelerated pace:

Sprint Planning
Daily Scrums
Product Backlog Refinement
Sprint Review
Sprint Retrospective

Artifacts:

Product Backlog
Definition of Done
Working Agreement
Release and Sprint Goals
Velocity and Burn Down Charts

Sarah Rasmussen is currently working at an insurance and financial services company and is Senior Manager of Data Management within the Enterprise Data & Analytics (ED&A) organization. Recent focused efforts include data leadership on a finance transformation program as well as the product owner for various MDM efforts. Sarah’s current focus is on further establishing the Data Governance program.

Her interest in data was established as her IT career evolved from developer to systems analyst to managing an Enterprise Data Administrators and Architect team for many years. Her current role relies heavily on a foundational understanding of the importance of and manner to which to apply proper data governance and management to data assets.