EXPLORING THE CAVERN OF DATA GOVERNANCE

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1 EXPLORING THE CAVERN OF DATA GOVERNANCE AUGUST 2013 Darren Dadley Business Intelligence, Program Director Planning and Information Office SIBI

2 Overview SIBI Program Methodology 2

3 Definitions: & Governance The planning, execution and oversight of policies, practices and projects that acquire, control, protect, deliver, and enhance the value of data and information assets. (*) Governance The exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets. (*) (*) DAMA International

4 Governance Challenges Key reasons for Failure (*) Governance Overview - Assign sponsor - DG Forums - Personal development plans - KPIs - Education - Best practices - Bench marking - Leverage other successes Lack of Ownership Ownership, responsibility and accountability not assigned. Lack of Awareness Executives and key stakeholders of data management capabilities have a lack of knowledge and awareness of DG. Lack of Accountability Accountability not assigned to each process - RACI - stewards - Personal development plans - KPIs Failure to Execute Lack of knowledge and Understanding by Senior (i.e. skills requirements, strategic outcomes, process improvement) leads to a failure to execute. Governance Challenges Task is overwhelming DG is too big for any one person to accomplish. Adequate resources are not assigned. - Pilot projects - Series of manageable projects - Identify key areas of concern - Split the tasks - Identify and assign resources - Training - Education - Communications - Workshops (*) Adapted from 2011 Baseline Consulting Group, Inc. 4

5 Governance Strategy What is Governance for the University Develop processes Identify a key initiative as a Pilot Define KPIs as measures for success Educate and engage stakeholders Document improvements and processes Communicate success SUCCESSFUL DATA GOVERNANCE Develop DG vision statement in line with University s strategic vision Define DG Scope DG with context of University Define Governance Framework Define DG organisation Define roles and responsibilities (RACI) Select Pilot area Workshop to identify and develop KPIs Determine accountability for KPIs Identify KPI benefits and ROI Define Pilot group Develop training plan Develop communications and engagement plan Educate stakeholders about DG Review and define process maps Establish SOPs (standard operating procedures) Develop review process Communicate success to key stakeholders and broader audience ( , bulletin, newsletters) Managing Expectations 5

6 Governance vs. Governance (Organisation and Activities) Strategy Organisation and roles Deliverables and standards Projects and services Issues management Creating guiding principles asset valuation Provide Guidance Create & Implement Deliverables Provide Feedback Track Progress (Execution) profiling quality monitoring cleansing Semantic rules enrichment Business rules creation & maintenance Enterprise data modeling Metadata definition Business glossary definition archival Backup and Recovery Authentication 6

7 Overview (DMBOK) Functions Architecture Integration Control Delivery Analysis Measurement Improvement Meta Quality Architecture Development Enterprise Modelling Value Chain Analysis Modelling base Design SDLC Implementation Acquisition & Storage Backup & Recovery Content Retrieval Retention Document & Content Warehousing & Business Intelligence Governance Reference & Master Security base Operations Acquisition Recovery Tuning Retention Purging Standards Classification Administration Authentication Auditing Architecture Implementation Training & Support Monitoring and Tuning External Codes & Internal Codes Customer Product Dimension 7

8 Overview Current focus for SIBI Governance Security Visibility Quality and Profiling Master Metadata & Business Glossary University of Sydney Governance SIBI 8

9 University of Sydney Framework Deliverables Activities Practices & Techniques Overview DMBOK 7 Environmental Elements Strategy People Organisation & Culture Roles & Responsibilities Organisation & Culture Goals & Principles Roles & Responsibilities Technology Process Technology Goals & Principles Activities Deliverables Practices & Techniques Provide a consistent way to describe and strategically plan each function Technology 9

10 DMBOK 7 Environmental Elements Overview Goals & Principles The directional business goals of each function and the fundamental principles that guide performance of each function. Activities - Each function is further decomposed into lower level activities (tasks and steps) Deliverables - The information and physical databases and documents created as interim and final outputs of each function. Some are considered essential, some are generally recommended, and others are optional depending on circumstances. Roles and Responsibilities - The business and IT roles involved in performing and supervising the function and the specific responsibilities of each role in that function. Many roles will participate in multiple functions. Practices & Procedures - Common and popular methods and techniques used to perform the processes and produce the deliverables. Risks and issues management. Technology - Categories of supporting technology (primarily software tools), standards and protocols, product selection criteria and common learning curves.. Organisation and Culture - These issues might include: - Reporting Structures, Teamwork and Group Dynamics - Budgeting and Related Resource Allocation Issues - Authority & Empowerment - Shared Values, Beliefs, Expectations & Attitudes - Change Recommendations - User engagement: communications / training / education 10

11 Governance University Organisation & Culture Governance Overview Organisation Deans of Faculties and Directors of Professional services Units, e.g. Finance, Research, HR, ICT Governance Committee (DGC) Own the data governance strategy Promote, endorse and approve the development and enhancement of the data governance management framework Directors, Heads of department, Managers of functional areas Support the DGC, by implementing and refining the data ownership, data stewardship and data custodian roles throughout the University. Provide Subject Matter Expert (SME) knowledge and support to the data governance strategy Owners Group (DOMG) Modellers Information / Architect Operating model Arbiters & escalations points Governance organisation members Roles & Responsibilities Terms of Reference ownership and responsibility Supported by: Integration Specialists Stewards base Administrators Quality Specialists 11

12 University Principles and Goals (recommended) Overview Governed Managed Trusted Principles Re-used Valued Shared Trusted. We trust in our information. Access to and use of data will promote trust and confidence through adherence to relevant Governance Policies and procedures, privacy, confidentiality and security requirements. Valued. is valued as a strategic resource and an asset. As a result, data and information will be of high quality, accurate, relevant, timely and support confident business decisions. Shared. Information and data is accessible, transparent and available to be shared as part of the University s sharing of information obligations to; the community, staff, students, researchers and alumni. Re-Used. and information should be obtained from a single authoritative source. and information is collected in a consistent manner and is available to be used for different purposes with confidence. Managed. and information is managed throughout its lifecycle and is compliant. Information Procedures and practices are standardised and applied across the University and apply to all involved in the data management lifecycle. Governed. and information is governed in accordance with the roles and responsibilities as defined in the University s Governance Framework, the University s strategic goals and in compliance with the requirements of Law. 12

13 Deliverables, Activities, Practices & Techniques Overview 13

14 Overview DMBOK Functions Architecture Integration Control Delivery Analysis Measurement Improvement Meta Quality Architecture Development Enterprise Modelling Value Chain Analysis Modelling base Design SDLC Implementation Acquisition & Storage Backup & Recovery Content Retrieval Retention Document & Content Warehousing & Business Intelligence Governance Reference & Master Security base Operations Acquisition Recovery Tuning Retention Purging Standards Classification Administration Authentication Auditing Architecture Implementation Training & Support Monitoring and Tuning External Codes & Internal Codes Customer Product Dimension 14

15 Quality Definition Planning, implementation and control activities that apply quality management techniques to measure, assess, improve and ensure the fitness of data for use.* *Source: DAMA-MBOK

16 Principles University of Sydney Quality Framework HR Pilot Vision *** Develop vision for Quality Mgmt. and for Pilot with HR data. (workshop) Goals Organisation & Culture Change Pilot group structure Risk Matrix Information Compliance Privacy Govt. Legislation Internal Audit External Audit Deliverables Issues Log Critical success factors User Engagement Activities Accuracy Authority & Empowerment Expectations & Communication Attitudes Education Comms Practices & Techniques Completeness Consistency Integrity Timeliness Roles and Responsibilities Roles Steward Owner Sponsor Forums SIBI Program Board Validity Custodian BOG Technology: Profiling (Informatica), cleansing (IDQ-Informatica)

17 Quality Quality Dimensions Accuracy Does the data accurately represent reality or a verifiable source? Completeness Is all necessary data present? Consistency Are all data elements consistently defined and understood? Integrity Is the structure of data and relationships among entities and attributes maintained consistently? Timeliness Is data available when needed? Validity Do data values fall within acceptable ranges defined by the business? 17

18 Quality Methodology - Roadmap Technology IDE Informatica Profiling tool Enables data profiling and analysis with the flexibility to filter and drill down on specific records for better detection of problems. IDQ Informatica Quality tool Enables architects and developers to discover and access all data sources, to improve the process of analyzing, profiling, validating, and cleansing data. Activities 1. Promote DQ Awareness 2. Define DQ Requirements Identify known data issues Extract & provide data 3. Profile, Analyse & Assess DQ 4/5.Define DQ metrics & Business rules 6. Test & validate DQ Requirem. 7. Set & evaluate DQ service levels 10. Clean & correct DQ defects 11. Design and implement DQM procedures (SOPs) Deliverables Vision statement DQM Framework RACI files Issue Log Baseline Updated Issue Log Scorecard Report Recommend Actions Actions: - Training / education / comms - Business Processes Improvement (SOPs) - Validation (data entry process) Control Activities 8. Continuously measure and monitor DQ 9. Manage DQ issues 12. Monitor operational DQM procedures and performance Activities for DQ Pilot Activities for DQ methodology 18

19 Overview Next Steps 19

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