Implementing a Data Governance Initiative



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Transcription:

Implementing a Data Governance Initiative Presented by: Linda A. Montemayor, Technical Director AT&T

Agenda AT&T Business Alliance Data Governance Framework Data Governance Solutions: o Metadata Management Solution o Analytical Master Data Management Solutions o Data Quality Solutions Lessons Learned Critical Success Factors 2

AT&T Business Alliance 3

The Need for Change Common Problem Statement: Approach to establishing data sources is silo d and lacks cross-functional collaboration to serve the needs of many Current Departmental/Project Approach to Business Intelligence Complete data is not readily available Not operating as One Enterprise Silo d projects and funding Multiple stored copies of source data Inefficient use of IT resources Limited common data governance and stewardship No common base from which to draw info Incomplete data and analysis Duplication of data and conflicting versions of the truth Possible inaccurate decisionmaking Long solution delivery times Cost duplication This leads to Abandoned projects 4

The Business Alliance What is it? o A joint business and IT coalition o A cross-organizational partnership What does it do? o Avoids execution of projects in isolation o Sets priorities among new and existing projects o Ensures Business Intelligence (BI) data is available to meet the business needs 5 Alliance Teams o Leadership Team o Working Team o Business Alliance Management Team

Changes Required for Success Fundamental Changes Current State Future State 1 Funding Model Client Sponsored & Funded Corporate Sponsored & Funded 2 Governance Client/Project Based Cross-Organizational Business Alliance 3 Scope of Requirements Departmental Data Needs Comprehensive Data Needs 4 Delivery Plan Silo d Project Releases Coordinated Roadmap 6

Business Alliance Challenges o Formulating an approach for such a large task o Balancing resources focused on program vs. sustainment efforts o Getting momentum going o Obtaining consensus across business stakeholders and IT o Ongoing communication of the end state vision Opportunities o Establishing a culture of working together to achieve the vision o Strengthening partnership between business and IT o Setting precedence for how large initiatives operate in the future 7

Data Governance Framework 8

Building the Capability Establish Organization Refine Establish Governance Rhythms Refine Operationalize Governance 9

Alliance Data Governance Charter The Data Governance Charter defines the team s: o Mission o Vision o Scope 10

Data Governance Framework Challenges o Establishing a charter while trying to define the end state vision o Learning from other cross-functional governance organizations o Staffing the right resources on the team o Balancing multiple work streams (time management) o Serving cross-organizational needs (e.g., Finance, Marketing) Opportunities o Defining your own success criteria o Learning opportunities for everyone involved o Establishing a common set of data governance policies and processes o Providing the business with data knowledge they didn t have before o Setting a standard for others to follow 11

Data Governance Solutions 12

Capabilities Data Governance Operations Responsible and accountable for defining, establishing and managing the Alliance Data Governance Charter, Scope, and Operating Model; managing and prioritizing requests for service; and all Alliance Data Governance related training and communications. Key Benefits: Centralized, cross-organizational team provides oversight of data ownership, governance, quality and controls Operating model with roles and responsibilities clearly defined Training materials available to provide quick on-boarding of resources Develop, standardize and maintain a well-defined, common, metadata management solution that addresses technical and business metadata Metadata Key Benefits: Minimizes time spent trying to understand the data by having access to documented definitions, business rules and data lineage Provides visibility to metadata via user friendly web interface 13

Capabilities, continued Analytical Master Data Establish and maintain meaningful ontologies and/or semantics, providing a clear, accurate and consistent view of data shared across systems/platforms. Key Benefits: Ability to leverage data values with common meanings across the enterprise, minimizing confusion and need for reconciliation Modifications to data relationships managed in one location and applied in a timely manner Easy to use, business managed and defined data hierarchies Data Quality Process controls, both technical interface and user defined controls/audits, to ensure accuracy, completeness & usability of the data Key Benefits: Faster identification of data issues allowing for mitigation and timely resolution Increased data accuracy Builds trust 14

People, Process, and Technology All components are necessary for delivering a complete, end to end, data governance solution Process People Technology 15

Business Requirement Categories o Metadata Management o Data Lineage Management o Data Stewardship o Training and User Documentation o Sustainment o Reference Data Management o Hierarchy Data Management o Workflow Management o Data Governance Policies o Data Quality o Usability o Data Search o Data Editing o Security o Maintainability 16

Data Governance: Metadata Management Solution Challenges o Deploying a tool (technology) does not equate to the deployment of the full data governance solution (people, process, technology) o Understanding the concept of business terms is difficult o Managing number of participants in business term vetting sessions o Organizing the Business Data Stewards o Ensuring established processes are followed o Establishing an interim process for metadata capture prior to tools deployment and reaching steady state o Establishing a strategy to migrate metadata from existing metadata repositories and into the enterprise tool set 17

Data Governance: Metadata Management Solution Opportunities o Simplifying, streamlining, and automating business activities and metadata management processes o Building a strong partnership (IT and business) o Providing input to process that will be extensible beyond the initial scope o Establishing a domain of metadata experts that reside within the business o Contributing to the increase in knowledge and understanding of data assets across the enterprise 18

Lessons Learned 19

Lessons Learned The identification of single points of ownership from both business and IT reduces the number of meetings and hours spent discussing and resolving work items and issues Factoring size and complexity of various groups helps to establish accurate delivery timelines Beginning with governing the data the business is most familiar with improves the understanding of the data governance processes and tools Providing more training on the differences between business and technical terms aids Business Data Stewards and Focus Teams on creating business terms for Business Glossary 20

Critical Success Factors 21

Critical Success Factors Officer sponsorship and commitment to fund Data Governance Initiatives Leadership team approval of: o Charter and Scope; plus published job descriptions, roles, and responsibilities Resources are assigned and team members are officially in place Requirements are documented and approved by all stakeholders Defined and managed timeline for delivery of capabilities that meet overall objectives Acceptance of the delivered technical solutions Data Governance team drives business adoption and use of the Data Governance infrastructure Data Governance team members feel they are well engaged, aware of key activities, and can be successful in performing their data governance roles and responsibilities Business stakeholders are enabled with the information necessary to effectively and positively change how they view, use and support common enterprise data 22

Thank you! Linda A. Montemayor AT&T, Technical Director LL5253@att.com 23