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Is Your Agency Data Challenged?

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Federated data organizations in public sector face more challenges today than ever before. As discovered via research performed by North Highland Consulting, these are the top issues you are most likely experiencing:
• Knowing what data is available to support programs and other business functions
• Data is more difficult to access
• Without insight into the lineage of data, it is risky to use as the basis for critical decisions
• Analyzing data and extracting insights to influence outcomes is difficult at best

The solution to solving these challenges lies in creating a holistic enterprise data governance program and enforcing the program with a full-featured enterprise data management platform. Kreig Fields, Principle, Public Sector Data and Analytics, from North Highland Consulting and Rob Karel, Vice President, Product Strategy and Product Marketing, MDM from Informatica will walk through a pragmatic, “How To” approach, full of useful information on how you can improve your agency’s data governance initiatives.

Learn how to kick start your data governance intiatives and how an enterprise data management platform can help you:
• Innovate and expose hidden opportunities
• Break down data access barriers and ensure data is trusted
• Provide actionable information at the speed of business

Published in: Software
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Is Your Agency Data Challenged?

  1. 1. Is Your Agency Data Challenged? Kick start your data governance initiatives with DLT Solutions July 2015
  2. 2. • Federated data organizations in public sector face more challenges today than ever before. As discovered via research performed by North Highland Consulting, these are the top issues you are most likely experiencing: – Knowing what data is available to support programs and other business functions – Data is more difficult to access – Without insight into the lineage of data, it is risky to use as the basis for critical decisions – Analyzing data and extracting insights to influence outcomes is difficult at best 7/20/2015 DLT Solutions LLC - Proprietary & Confidential 2
  3. 3. • The solution to solving these challenges lies in creating a holistic enterprise data governance program and enforcing the program with a full-featured enterprise data management platform. • Kreig Fields, Principle, Public Sector Data and Analytics, from North Highland Consulting and Rob Karel, Vice President, Product Strategy and Product Marketing, MDM from Informatica will walk through a pragmatic, “How To” approach, full of useful information on how you can improve your agency’s data governance initiatives. 7/20/2015 DLT Solutions LLC - Proprietary & Confidential 3
  4. 4. • Learn how to kick start your data governance initiatives and how an enterprise data management platform can help you: – Innovate and expose hidden opportunities – Break down data access barriers and ensure data is trusted – Provide actionable information at the speed of business 7/20/2015 DLT Solutions LLC - Proprietary & Confidential 4
  5. 5. 5 Data Governance for Govt. Kreig Fields Principal, Public Sector Data & Analytics North Highland
  6. 6. 6 Agenda 1. Why data governance for public sector? 2. Establishing a data governance organization 3. Building a data governance solution 4. Do’s and don’ts 5. Open questions
  7. 7. 7 Why data governance for public sector? Data governance enables cohesive, consistent and reliable data across all of these data perspectives • Federated governance approach in public sector leads to fragmented data perspectives HQ District1 District2 District3 District4 District5 District6 AcquisitionACQ ACQ ACQ ACQ ACQ ACQ Proj…Proj Proj Proj Proj Proj Proj
  8. 8. 8 Common gaps in enterprise data
  9. 9. 9 Challenging but not impossible • Federal Government has defined a governance approach for aligning data and applications across the federal government › Uses Federal Enterprise Architecture (FEA) Link to Federal Enterprise Architecture information › The DoD uses Department of Defense Architecture Framework (DoDAF) Link to DoDAF information Proper data governance and tools are essential to managing these issues!
  10. 10. 10 Data Governance • Decision-making and oversight • Uses a Committee to make decisions and to provide strategic direction Data Stewardship • Formally making someone accountable for data integrity • Manages internal data subject area and it’s impact to the business • Coordinates with colleagues and recommends operational changes needed to improve data governance Data Management • Day to day execution of the Governance rules • Responsible for the day to day data management activities • Receives direction and guidance from data steward Establishing a data governance organization
  11. 11. 11 Systems Model Projects Model Biz Function Model Subject Area Model Biz Process Model Sample Data Governance/Stewardship Models
  12. 12. 12 Building a data governance solution
  13. 13. 13 Start by assessing where you are. Data Quality Data Integration Data Strategy and Architecture Master Data Management Metadata Management Analytics Security and Privacy Dashboards Scorecards Reporting Projects, interviews, and surveys • Do not let perfection stand in the way of progress Public Sector
  14. 14. 14 • Address data reliability and consistency issues • Improve business visibility and decision-making • Streamline time/effort required to share information • Increase the organization’s understanding of the business in order to promote transparency and efficiency • Drive increased accuracy, timeliness and the precision with which teams can discuss and collaborate on business issues and opportunities • Communicate and coordinate activities such that rework and duplicative calculations, analysis, and reporting are either eliminated or recognized as necessary. • Facilitate purposeful and coordinated ad hoc analysis • Shift focus from data entry applications, to exploiting the value of information for our business and customers. Data Governance: Do’s
  15. 15. 15 • Introduce cumbersome and unwieldy processes • Create redundant processes • Focus on just the technology, but on how business can achieve the maximum benefits of technology. Data Governance: Don’ts
  16. 16. Thank You
  17. 17. Accelerating and Enabling a Sustainable Data Governance Program in Government Rob Karel, Informatica VP Product Strategy and Marketing, Information Quality Solutions
  18. 18. Agencies Face Data Challenges 20 Valuable information exists, but trapped in legacy systems or not digitized New sources and huge volumes with up to 80% unstructured Long lifespan of data, due to retention regulations, adds storage stress… …But short life of usable data due to data degradation No data map to classify types and importance of data Data governance, including data policies, needed Data stewardship and master data management non-existent Proliferation of duplicate and uncleansed data
  19. 19. With Many Unanswered Questions 21  What is the quality of existing and new data?  How do we define quality anyway?  Do we capture data appropriately?  How much data must we store, and in what format?  How long must we keep the data?  Who owns the data?  How do we secure and address privacy of personal data?  Where’s this information coming from? Should I trust it?  Who needs what data, and why?  How do we balance real-time vs. right-time data delivery?  Does data change frequently? And that’s just the tip of the iceberg
  20. 20. Data Governance is a Business Function Data governance should be managed as a business function, no different than Finance or Human Resources
  21. 21. Data Governance Maturity Stages Fragmented Holistic IT-drivenBusiness-driven 0: Unaware • No activity 1: Initial • Ad hoc 2: Repeatable • Pilot 3: Defined • Project 4: Managed • Program 5: Optimized • Function Fragmented Holistic IT-drivenBusiness-driven IT efficiency and compliance Cost control, business efficiencies & risk reduction Greater efficiency, compliance and support mission-critical objectives Innovation, automation, economy of scale and agility
  22. 22. Data Governance Maturity Benchmarks (as of 7/15/2015) Public sector maturity below x-industry average
  23. 23. Data Governance is not – and should Never have been – About the Data… …the vision must be to improve the business processes, decisions and interactions trusted, secure data enables!
  24. 24. The Ten Facets of Data Governance People Vision and Business Case Tools and Architecture Dependent Processes Measurement Org Alignment Change ManagementPolicies Defined Processes Program Management
  25. 25. Data Governance Roles and Responsibilities Steering Committee Business and IT Stewards Data Governance Leader/Driver Executive Sponsor(s) • Facilitation • Communication • Measurement • Escalation • Business case Drive X-functional: • Prioritization • Resource allocation • Approvals • Broader funding • Enforce collaboration • Vision • Evangelism • Funding • Remove barriers • Analysis • Definition • Business/IT liaisons • Education • Ensure compliance • Mitigation
  26. 26. Flavors of Data Governance Measurement  Operational monitoring  Service Level Agreements (SLAs)  Program effectiveness  Business Value/ROI Data Governance Leader, LOB and Data Stewards Executive Sponsors and Steering Committee
  27. 27. Sample Key Performance Indicators KPI Name KPI Type KPI Description Level of DG program influence Program effectiveness # of lines of business, functional areas, system areas, project teams and other parts of org that have committed stewardship resources or sponsorship DG interactions Program effectiveness Capture all types of value-added internal interactions such as training, consulting and project implementation support Issue resolution Program effectiveness Categorize and track status of all issues that come in to the data governance function External validation Program effectiveness Industry awards, benchmarking against peers, thought leadership via speaking tours Data quality metrics Operational Monitoring of data accuracy, completeness, integrity, uniqueness, consistency, standardization, and other baseline DQ metrics Policy compliance Operational Audits ensuring compliance with privacy, security, retention and other regulatory policies. Recovery time SLA A contracted agreement with the business on how long before a data exception will be mitigated Data latency SLA A contracted agreement with the business on how quickly a data update or insight will be delivered to a dependent process or decision-maker Compliance Biz value Reducing penalties by ensuring regulatory compliance; reducing enterprise risk (e.g., contractual, legal, financial, brand) Cost savings Biz value Lowering costs (e.g., business, labor, software, hardware) Spend optimization Biz value Optimizing spending (e.g., procurement, supply chain, services, labor) Efficiency improvements Biz value Improving operational efficiencies (e.g., employee, partner, contractor);. Revenue growth Biz value Increasing top-line revenue growth; Customer satisfaction Biz value Optimizing customer experience and satisfaction
  28. 28. Data Governance Process Stages Discover • Data discovery • Data profiling • Data inventories • Process inventories • CRUD analysis • Capabilities assessment Define • Business glossary creation • Data classifications • Data relationships • Reference data • Business rules • Data governance policies • Other dependent policies • Key Performance IndicatorsMeasure and Monitor • Proactive monitoring • Operational dashboards • Reactive operational DQ audits • Dashboard monitoring/audits • Data lineage analysis • Program performance • Business value/ROI Apply • Automated rules • Manual rules • End to end workflows • Business/IT collaboration Apply Data Governance Apply Measure and Monitor Define Discover IT Business Collaborate
  29. 29. Informatica Platform Built to Support Holistic Data Governance Apply Data Governance Apply Measure and Monitor Define Discover IT Business Discover Define Measure and Monitor Apply Collaborate Business Process Management
  30. 30. Architectural Scope of Data Governance Enterprise Data Warehouse BI/Analytics Performance Management MobileShared Capabilities • Metadata/lineage • Business glossary • BPM/Workflow • Connectivity • Services • Collaboration • Monitoring • Policy management • Stewardship • Discovery • Security • Canonical Model Cloud Social Hadoop Big Data Enterprise Integration DQ, Profiling CEP and Business Rules MDM/ Reference Data Mgmt Business, Data and Process Modeling Information Security/ ILM Data Virtualization Legacy Web Enterprise apps On premises (machine) Big Data 3rd party/Market data
  31. 31. Identify candidate business opportunities 1. What are the top business imperatives as defined by your most senior leadership? 2. What organizational business processes, decisions and stakeholder (e.g., citizen, partner, employee) interactions are most important in support of these top imperatives? 3. What data and applications are used to support those processes, decisions and interactions? Data Scope thousands of “relevant” data items to dozens or hundreds of “critical”
  32. 32. Use Discovery Processes to prioritize roadmap 4. What upstream people, systems, and processes create, capture, and update that data? 5. What is the business end user’s level of confidence in the security and trustworthiness of that data? Repeat process and reassess priorities ongoing (quarterly or bi-annually at minimum) Data
  33. 33. 1 2 3 4 5 6 7 8 9 10 0.00 1.00 2.00 3.00 4.00 5.00 6.00 0.001.002.003.004.005.006.00 BusinessValue High <--- Investment & Effort ---> Low Business Opportunity Name Consider Prioritize ExperimentIgnore # Business Opportunity Name 1 Reduce eDiscovery risk 2 Improve customer satisfaction scores 3 Implement shared services /COE for data management 4 Improve financial reporting 5 Secure sensitive data 6 Optimize supply chain 7 Reduce costs and inefficiencies through modernization of enterprise applications 8 Reduce waste, fraud & abuse 9 Reduce costs through data Center Consolidation 10 Introduce new service channels e.g. mobile Consider Standardizing Process For Business Opportunity Prioritization
  34. 34. Free Tools Available on GovernYourData.com
  35. 35. Contact Us DLT Solutions | Infrastructure Performance Management • Visit us on our website: – http://www.dlt.com/brands/informatica • Reach out to us via email: – ipm@dlt.com • Find us on social media: 7/20/2015 DLT Solutions LLC - Proprietary & Confidential 37
  36. 36. Learn More • For more information, click below to download the full on-demand webinar: 7/20/2015 DLT Solutions LLC - Proprietary & Confidential 38

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