The Key Components of a Data Governance Program. John R. Talburt, PhD, IQCP University of Arkansas at Little Rock Black Oak Analytics, Inc

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1 The Key Components of a Data Governance Program John R. Talburt, PhD, IQCP University of Arkansas at Little Rock Black Oak Analytics, Inc

2 My Background Currently University of Arkansas at Little Rock Acxiom Chair of Information Quality Director of the Information Quality Graduate Program Black Oak Analytics, Inc. Co-Founder Chief Scientist Previously Acxiom Corporation Business Leader for Data Research and Development Leader for Product Development and Innovation 2

3 Data Governance 3

4 Data Governance Framework for defining roles and responsibilities and the rules for making decisions about data management in an organization Data Management is the decision you make Data Governance is the structure for making them It is fundamentally about Communication & Control A single-point of communication about data Data dictionary, business rules, DQ rules, compliance rules, etc A single-point of control over Changes to data Changes to data processes 4

5 Why is it Important Data Governance is the primary tool for managing information as an enterprise asset. It moves information quality from being a project-to-project effort to being an ongoing business function Done properly it can Reduce the cost of operations Increase revenue Reduce the risk of data leakage Avoid fines and penalties for non-compliance to regulation 5

6 Based on the Principle of Data Stewardship Recognition that the information is an organizational asset No one person, department, or group owns the data they are only stewards (caretakers) of the data on behalf of the organization Therefore, data management decisions must take into account the potential impact on all parts of the organization 6

7 Data Change Management

8 Data Change Management Follows the principles of software change management All changes to the data architecture must be proposed to, and approved by, the DG Council Changes to critical data items are done to one golden copy (master copy) of the data All users of the data reference the master copy rather than managing their own copy of the data 8

9 Unilateral Change Change Made by Dept A Department A Dept B uses data from Dept A Department B Department A Improves its Process Change Breaks Process in Department B No Warning! 9

10 Notification and Agreement An essential part of data governance is to avoid the unilateral change scenario Governance Council with representatives from all parts of the organization Any changes must first come to the Council Council agrees with or denies change or suggests alternative Resolves conflicts on data management 10

11 Managed Change Dept A Proposes Change Data Governance Council Representatives from Dept A Dept B Dept C Representative from Dept B warns of problem Avoid Problem Dept A & Dept B Both Processes Improve Dept A and Dept B Jointly Design Alternate Solution 11

12 Structure and Components

13 Setting Up a Program Define Your Mission Decide on Initial Focus Policy-Standards-Strategy, Data Quality, Privacy/Compliance/Security, Architecture/Integration, Data Warehouse and BI, Management Alignment Document the program structure, the governing polices, and procedures for operation Develop a Value Statement Prepare a Roadmap Plan and Fund Design the Program Deploy the Program Govern the Data Monitor, Measure, Report 13

14 Archetypal 3-Part Organizational Structure Data Governance Authorities Data Governance Office (DGO) Data Governance Council Embedded Data Governance and Stewardship Workers 14

15 Key Data Governance Components Business Glossary Technical Metadata Data Profiling Tool Data Quality Metadata Master Data Management Reference Data Management Information Policy Management 15

16 Business Glossary (Business Metadata) The starting point for implementing a DG program Defines key business concepts and terms, e.g. customer, customer identifier, cash, agency, branch, Usually organized into categories, e.g. accounting, marketing, Relate concepts to specific entries in the data dictionaries Each term has several roles with specific people assigned to each role Data Steward Mary Ellen, Data Owner José Macho, Each term can have several relationships to other data artifacts Data dictionary entries, reference tables, 16

17 Technical Metadata Logical Data Models Database schemas Physical Data Models Data dictionaries File layouts Linked with Business Glossary Terms (Glossary) Customer Identifier (DD Application A) CYCTOID (Glossary) Customer Identifier (DD Application B) CLIENT_NUM 17

18 Data Profiling Tool Vital for data discovery Discovering the true metadata Discover data anomalies and outliers Discover hidden sensitive data Discover hidden relationships Don t rely on SQL queries Use a real data profiling tool Column profiling Value and pattern profiling Data integrity profiling 18

19 Data Quality Metadata Transform data into standardized formats Create and manage data quality metrics Create a Data Quality Scorecard Highlight the Financial Impact of Poor Data Quality Time Series Analysis Manage data quality exceptions 19

20 Master Data Management Define business terms used in the MDM Hub Manage entity relationships Manage record matching rules Detect and manage duplicates Manage master data workflows 20

21 Reference Data Management Build an inventory of Code Tables Agree on the Master List of Value for each Code Table Manage hierarchy of code tables 21

22 Master and Reference Data Management All Changes Master Data No Changes System A System B No Changes Consistent Values 22

23 Information Policy Management Manage policies, standards, and processes in the Business Glossary Manage business rules Monitor and report on compliance Manage data issues 23

24 Business Rules A business rule is an authoritative principle or guideline that describes business interactions Establishes rules for actions and resulting data behavior and integrity 24

25 Business Rule Collection Collect business rules to provide input for Creating necessary IQ checks Analyzing the results of the assessments. The lack of well-documented business rules often plays a part in IQ problems. 25

26 Central Tracking System for Data Issues Tracking the number and nature of issues is an important metric for the success of a DG program Gives the DG council an overall view of data issues across the enterprise Alerts the DG council to possible data risks Allows the council to better prioritize improvement projects to derive the highest benefit 26

27 Promotes Communication Data Governance Council can not only prevent adverse events from unilateral change Can also promote communication to Eliminate unnecessary redundancy (Build Trust) Uncover data quality problems at the enterprise level Suggest improvements in the information architecture that benefit the entire organization 27

28 Free Advice

29 Introducing Data Governance Emphasize the positive aspects, not the procedures and control Explain the VALUE to enlist sponsors When talking to key stakeholders ask Do you want to be consulted about changes before they are made, or do you just want to be informed after they are made? Measure Success Results Metrics Value Metrics 29

30 Buy a Data Governance Tool Trying to use spreadsheets just won t work Need software that integrates all of the data governance components Very complex to build, many good vendor solutions ASG, Collibra, Global ID, IBM, Informatica, Tool should enable data stewardship processes Enforce procedure and policy Save change history Maintain synchronization of the related pieces 30

31 Five Most Common Mistakes Lack of Authority No written policies, standards, guidelines, rules, or DG agreements Inadequate Infrastructure Lack of funding, allocation of time for DG work, no admin staff Politics and Power Struggles DG should be neutral territory Lack of Participation Need a critical mass to succeed Perceived as Delivering Low Value Important to have value metrics 31

32 Questions and Discussion

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