Data Governance and Data Stewardship

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1 Data Governance and Data Stewardship 12th Annual Privacy and Security Conference February 16-18, 2011 Victoria Conference Centre, Victoria, BC Marc Smith, Principal Solutions Architect SAS Canada Copyright 2010 SAS Institute Inc. All rights reserved.

2 Why Data Governance Enable strategy, drive value with data assets See across the enterprise, breakdown silos Regulatory compliance 2

3 Scope of your Data Governance Information Value Chain Descriptive quantitative, qualitative Data Information Facts Metrics Insight experience instinct beliefs Knowledge Action decision innovation achievement discovery Outcome 3

4 Spectrum of Data Governance Programs non-invasive data governance* collaborative data management policy definition and enforcement * Non-Invasive Data Governance is a trademark term of Robert S. Seiner and KIK Consulting. 4

5 Ownership Leadership Tied to value, clear goals, make it strategic Teamwork and corporate culture Data, processes, and technology Careful with the G word really, it s leadership 5

6 Data Governance vs. Data Management Data Governance Executive Leadership Team DG Executive Sponsor Data Owners Data Owners Data Owners Data Owners Data Steward Data Steward Data Steward Data Management Data Modeling Data Administration Master Data Management Data Quality Data Integration Privacy and Security 6

7 Examples 7

8 Large west-coast US County Highlights Enable evidence based policy making Remain compliant with confidentiality and privacy rules Improve service coordination Identify duplicate services Cost avoidance, cost savings, improved service delivery Business Problem As the county attempts to integrate the provisioning of services for indigent adults, confidentiality and privacy rules impose significant barriers in sharing information across government agencies. The challenge is to implement evidence-based policies without compromising the privacy of the citizens that they serve. SAS Approach SAS provided the infrastructure and expertise to build anonymous record linkage (Statistical Linkage Key) method to integrate data across departments and with adult relief participants (cohorts). This record linkage method de-identifies personal information provided in administrative data. Results Able to provide policymakers with empirical information that can support the enhancement of existing programs for indigent adults and advance social policy making in the county. 8

9 Electoral Data Management and Readiness Branch National Register of Electors (the Voters List): Matching the Register to numerous data feeds, including» Provincial drivers information» Provincial death notices» Canada Revenue Agency De-duplication within the Register E-Registry (coming Fall 2011): Online public web-access to the Register.» Matching of Elector s name and address to the Register» Verification of inclusion on the voters list» Polling station information for Election Day Phase II (2012) to including update capability via the web 9

10 Alberta Health and Wellness Data Quality Framework Six Dimensions of Data Quality Accuracy How well information reflects what was supposed to be collected in context of existing standards and intended purpose(s) for use Consistency The ability to integrate an information asset with other information assets Timeliness The degree to which data are available for user needs within a reasonable time period Documentation How well an information asset is described in a consistent manner Accessibility The degree to which data can be retrieved (given security and privacy constraints) Relevance The degree to which a data element or an information asset are being collected according to its purpose or intended purpose. 10

11 Keep in Mind Data and Leadership are the most important prerequisites Make sure your targets are value based and strategic, have a goal in mind Don t boil the ocean, just drain a lake This is not business as usual - there is a historic opportunity to transform your industry! 11

12 Marc Smith, Principal Solutions Architect SAS Canada Copyright 2010 SAS Institute Inc. All rights reserved.

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