PM2: Using Data Delivery Lifecycles to Enable Data Strategy, Architecture, and Analytics
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  Gwen Thomas   Gwen Thomas
Corporate Data Advocate
IFC, Part of the World Bank Group


Monday, November 2, 2015
01:00 PM - 04:15 PM

Level:  Advanced

Data analytics and governance are gradually breaking down the traditional demarcation between "the Business" and IT. But it's an age-old struggle: Data management and governance workers often struggle in environments that define themselves as "The Business working with IT," with an underlying assumption that data will simply appear and take care of itself. Entire data-centric disciplines, knowledge sets, and task sets are shoe-horned into lifecycles and project plans focused on technology; the end result is that the organization faces major challenges in operationalizing their overall data strategy. Learn what happened when the speaker quit fighting and instead joined the discussion. From the perspective of an overall Data Strategy, these circumstances call for key components that need to be treated as standalone, but inter-related strategies. It needs a common organizational framework that calls out roles that might otherwise be obscured or overlooked. Key activities are needed for each strategy, then mapped to data-centric roles, and represented in both RACIs and work plans.

Lean about both necessary and optional data-centric activities within SDLCs and their parallel Data Delivery Lifecycles (DDLCs), including:

  • Preventative DQ controls to support Analytics
  • Activities for moving from silo architectures to system-of-system models
  • Demand management for foundational data projects
  • Increasing data management capabilities in multi-project environments
In addition, see how to use RACIs to map these activities to various roles:
  • Traditional IT project roles
  • Traditional IT functional roles associated with Business Systems and with BI/Analytics environments
  • COEs and working groups that deal with specialized supporting technologies, services, and repositories (ETL, SOA, BPM, MDM, CRM, Security, etc.)
  • Data Governance, Stewardship, Steering Committees
  • Data Management coordination ("A DM is to data what a PM is to projects")
  • Data Architecture & metadata
  • Risk Management, legal, compliance, and Internal Auditing
  • Leadership roles in Business, DM, and IT (because of need for "Tone from the Top")
This workshop, with example high-level strategies for the topics above, will provide a process for converting the strategy to a work plan, role descriptions for the involved groups, and also lists of key activities and example RACIs.

Gwen Thomas is a Data Governance pioneer, helping to define and evangelize the field. Founder of the Data Governance Institute (DGI) and primary author of the framework and guidance materials found at, she has influenced hundreds of programs around the globe. In the spring of 2013, Gwen joined the International Finance Corporation, part of the World Bank Group, as their Corporate Data Advocate.Earlier in her career, Gwen spent a dozen years working in the trenches and in management roles as a systems integration consultant and Knowledge Manager. has named her one of "17 Women in Technology You Should be Following on Twitter " (she's @gwenthomasdgi) and has included her in their Data Governance Gurus list.

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