Implementing a Successful Data Governance Program

Transcription

1 Implementing a Successful Data Governance Program Mary Anne Hopper Data Management Consulting Manager SAS #AnalyticsX

2 Data Stewardship #analyticsx SAS Data Management Framework BUSINESS DRIVERS DATA GOVERNANCE DATA MANAGEMENT METHODS SOLUTIONS

3 Data Stewardship Roles & Tasks #analyticsx SAS Data Management Framework BUSINESS DRIVERS Customer Focus Compliance Mandates Mergers & Acquisitions At-Risk Projects Decision Making Operational Efficiencies DATA GOVERNANCE DATA MANAGEMENT Program Objectives Guiding Principles Decision-making Bodies Decision Rights Data Architecture Data Warehousing & BI/Analytics Metadata Data Lifecycle Reference and Master Data Data Quality Data Administration Data Security METHODS SOLUTIONS People Process Technology Business Data Glossary Data Monitoring Big Data Management Data Lineage Data Visualization Data Profiling Data Integration Metadata Management Data Quality Data Exploration Data Virtualization Master/ Reference DM

4 The Data Governance Journey Plan the Program Design the Program Launch the Program Phased approach to identify business needs, address opportunities, and plan efforts

5 The Data Governance Journey Plan the Program Design the Program Launch the Program Define the objectives of the program and set a framework for how and when decisions will be made Initial Scope Objectives Guiding Principles Decision-making Bodies Decision Rights Roles and Responsibilities Program Charter

6 Prioritize the Challenges!

7 Business Value and Achievability

8 Prioritize the Challenges!

9 Defining DG Objectives What do we want to achieve with Data Governance? Can we measure against the objective?

10 Objectives - Samples Maintain a correct and consistent definition of the data and its business rules Increase the consistency, availability, usability, and quality of internal and external data Eliminate redundant or conflicting business processes and practices Provide a robust framework that enables sustainable execution across multiple data domains

11 Defining DG Guiding Principles Guiding principles are the set of common philosophies intended to direct a program or organization irrespective of day-to-day changes Ideally they will reflect the organization s values and goals Their purpose is to serve as a philosophical touchstone for questions or dilemmas during Data Governance deployment

12 Guiding Principles - Samples The customer will be top of mind Customer data attributes will be shared through a common process or interface Outcomes should enable a seamless, consistent experience for customers Systems of record will be held accountable for data quality Participation is mandatory

13 Enterprise Data Governance Program Management #analyticsx Organizational Structure - Sample Enterprise Data Governance Steering Committee Product /Item Customer Finance TBD Product/Item DG Council Customer DG Council Finance DG Council TBD DG Council DS Team DS Team DS Team DS Team Common Operating Framework & Processes Data Management Business Processes, Application & Systems, Organization

14 Organizational Structure - Sample DG Steering Committee DG Sub-Committee DG Office Data Management Data Steward Data Steward Data Steward

15 The Data Governance Journey Plan the Program Design the Program Launch the Program Determine how decision making bodies will operate and how compliance and progress will be measured Key Activities and Decisions Assign Decision Making Identify Key Participants Operating Procedures Key Workflows Communication and Training Metrics

16 DG Decision Making RACI Legend R = Responsible (Do the Work) A = Accountable (Ensure the Work is Done/Approver) C = Consulted (Provide Input) I = Informed (Notified, Not Active Participant)

17 Identifying the DG Actors

18 DG Operating Procedures - Sample Define DG Operating Procedures what the actors need to know to become operational

19 DG Workflow - Sample Define key DG workflows where the actors fit into the most important activities

20 Program Measurement - Sample Program measurement measure and monitor against established objectives

21 Roadmap - Sample

22 The Data Governance Journey Plan the Program Design the Program Launch the Program Begin execution of roadmap; start small and expand DG Onboarding Execute Operating Model Policy Development Benefit Measurement

23 What is a Policy? Policy Formal set of statements that define how the data resources will be used or managed Procedure Detailed instructions about how a policy is to be implemented Standard Required configuration that is considered best practice Best Practice Technique, method, process, or activity that is more effective at delivering a particular outcome than any other technique, method, process, etc Data Management Tactical execution and enforcement of data governance policies and standards

24 SAS Data Management Framework Policies can be broad or granular in nature depends on the organization Retailer will utilize a standard product-focused hierarchy to be called the Enterprise Product Hierarchy. Other user classifications or views may be used for specific business needs. Hierarchy structures will be sourced from a common location. The Data Governance Office, in partnership with the appropriate business entities and support from IT, will proactively assess, monitor, report, and improve data quality. For the purposes of this policy, data quality is defined as the conformance of data to the business definitions and the business rules (business metadata). Development process is still the same!

25 Policy - Sample Policy Component Sample Statement(s) Policy Objective Policy Procedure(s) Standard(s) Compliance Identify the business needs and the associated business usage of product hierarchies and categories - Define Retailer s supported hierarchies and categories - Identify usage - Document process to maintain and manage changes Provide foundation for detailed attribute definition and standardization - Core Attributes - Product Specific Selling Attributes Provide the process to measure compliance Retailer will utilize a standard product-focused hierarchy to be called the Enterprise Product Hierarchy. Other user classifications or views may be used for specific business needs. Hierarchy structures will be sourced from a common location All products will align to a standard product segment at product set-up in support of the Product Hierarchy. All products will align to one or more business focus areas. Product segment and business focus will determine data collection requirements, data management, process flow, decision rights, and data ownership. Segment Family Class Brick GTIN Product on-boarding aligned to standard hierarchy Legacy systems updated to align to product-focused hierarchy

26 Policy - Sample Policy Component Sample Statement(s) Policy Objective Policy Procedure(s) Standard(s) Compliance Understand and define data quality baseline. Define data quality measures. Ensure data quality issues are corrected at their source. The Data Governance Office, in partnership with the appropriate business entities and support from IT, will proactively assess, monitor, report, and improve data quality. For the purposes of this policy, data quality is defined as the conformance of data to the business definitions and the business rules (business metadata). The Data Stewards will evaluate the quality of the data in a specific focus area. The Data Steward will work with subject matter experts within the business to establish data quality measures and remediation steps for high impact data elements. The DG Office will work with data producers and data consumers to establish Data Quality SLAs The DQ process will follow the defined closed loop process. The common set of DQ tools will be utilized for DQ activities. Compliance is achieved for high-impact data elements when: Data is profiled Measures defined SLA defined Ongoing quality monitored

27 #AnalyticsX