1. Business Analysis Professional Development Day – Sep 2015 Data Governance and Cross-Functional Needs Neelam Mohanty

2. Agenda 2 What is Data Governance Goals of Data Governance -Eliciting definitions from a cross-functional group of stakeholders -Non-invasive data governance -Building a change coalition of data stewards Impact on Data Quality

3. 3 Examples of data governance Single Version of the Truth  600 individuals whose only role is Faculty  300 individuals whose only role is Staff  25 individuals are Staff but also are adjunct Faculty  75 individuals are faculty but also have a Staff role Total Faculty & Staff : 1000  675 counted as Faculty  325 counted as Staff 1,000 <> 1,100 Total Faculty  1,000 Total Staff  400 Source: University of Notre Dame Presentation HEDW 2013

4. How You Ask is as Important as What You Ask 4  Context Matters  Clarity Matters  The question matters Governance is as much about how you use the terms as it is about the terms themselves

5. Counting Problem 5

6. 6 Active Student Definition An individual who has been confirmed by an admitting office ( or other admitting authority), as recorded by the University Registrar, is considered an active student until he or she:  Graduates ( if degree-seeking)  Completes the academic term ( If non-degree seeking)  Withdraws or is dismissed by the University  Fails to enroll for a spring or fall academic term ( unless granted a leave of absence by a Dean)

7. Counting Problem 7

8. 8 Business Impact of Low Data Governance  Distrust of data coming from BI/DW system  No on-going responsibility for quality of a project after go-live  Continuous cleaning of data without putting in place preventive measures

9. Why does this challenge occur ? 9 Data is a “lateral” asset spanning multiple functional areas Each household brings their own ways of living, preferences, attitudes. A different level of cooperation and coordination is required to live together ( productively/peacefully) in the same house The problem is that our applications and business needs for information are integrated, but our behavior has not changed to work effectively in this world Source: SF DAMA Day 2006

10. Definition of data governance 10  Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. Source: searchdatamanagement.techtarget.com/Definition/0…  Data governance is the practice of organizing and implementing policies, procedures and standards for the effective use of an organization’s structured/unstructured information assets. Source: www.sdn.sap.com…  Data Governance: The execution and enforcement of authority over the management of data assets and the performance of data functions. Source: www.tdan.com/view-articles/5037  Data governance is the decision-making process that prioritizes investments, allocates resources, and measures results to ensure that data is managed and deployed to support business needs. Source: www.b-eye-network.com/view/8393 Multiple Definitions: pick the one that you like

11. Definition of data governance 11  Data governance recognizes that data is an important enterprise data asset and applies the same rigor to managing this asset as it does for any other asset Source: Jonathan Geiger  A program for defining information policies that relate to the constraints of the business Source: David Loushin  Execution and enforcement of authority over the management of data and data-related processes Source: Gwen Thomas  A process focused on managing the quality, consistency, usability, security, and availability of information Source: Alex Berson and Larry Dubov

12. Definition of data governance 12 Data Governance ensures that accurate information gets to the  right person, for the  right reason, at the  right time to make the  right decisions Here’s the one that I like : The 4 “R”s

13. 13 How do you justify a data governance program? Make your business case Is it compliance related?  Health Care - HIPAA (Health Information portability and accountability act)  Financial Reporting - SOX(Sarbanes Oxley Act of 2002)  Federal Information - FISMA (Federal Information Security Management Act of 2002)  Financial Institutions - GLBA (Gramm-Leach-Bliley Act)  Payment Card Processing - PCI DSS (Payment Card Industry Data Security Standard)  Higher Education - FERPA (Family Educational Rights and Privacy Act)  National Data Privacy Law  Data Quality Act  Patriot Act  Corporate Information Security Accountability Act of 2003

14. 14 How do you justify a data governance program? Make your business case  Reliable management reporting  Optimized business processes  Timely mergers and acquisitions  Reduced risk in customer and business data retention when stored per a defined data lifecycle  Master Data Management – Providing the golden record for customers, employees, products, members, providers etc. allowing for better customer service, ability to cross sell and upsell, visibility across multiple domains ( E.g. providers who are also members), correct addresses to mail campaigns, discount on CASS certified postal mail etc.

15. Process of data governance 15  Scope  Who has input  Who makes the decisions  Enforcement

16. Five dimensions to scope 16  Data  System  Business Process  Organization  Policy Type

17. Governance Model 17 Data DefinersData Users Data Producers Tactical Data Stewards (Cross Department/Business-Unit) Data Steward Coordinators Information Governance Council (Enterprise) ExecutivesSenior Managers Data Stewards/Trustees/Custodians/Guardians (Department or Business Unit Specific) Executive Sponsor(s) Strategic Tactical Operational EIM Council Business Unit Enterprise

18. 18 Executive Leadership Governance Managers /Process Owners Stewardship / Quality Management & Data Architecture Data Users Executive Sponsor & Strategic Level – Sponsors the Governance program – Provides support leadership and funds – Provides guidance and sets direction Program Level – Leads the governance program at a tactical level – Responsible for ensuring data governance process compliance at business entity level Execution Level – Does the actual Data governance activities – Works with the data owners and users to ensure data standards and quality – Works with Data architecture manager, data architects and data analysts for preparation of artifacts for governance Execution Plan Communication Path & Venues for Interactions Feedback Loop & Issue Resolution Enterprise Data Management – Data Governance Components

19. Example RACI MATRIX 19

20. 20 Questions? Contact me at neelam.mohanty@caresource.com