BEGIN:VCALENDAR VERSION:2.0 PRODID:-//hacksw/handcal//NONSGML v1.0//EN METHOD:PUBLISH BEGIN:VEVENT DTSTAMP:20260312T095452Z DESCRIPTION:Click for Latest Location Information: http://dgiq2021.datavers ity.net/sessionPop.cfm?confid=147&proposalid=13148\nNOTE: This 2-day semina r continues through Friday.\nData Governance is crucial to properly us ing your data and improving the quality of your data. And Data Stewardship is a critical piece of Data Governance — data stewards are your decision-makers about what data means, how it is derived, what rules to app ly to determine data quality, and what data quality issues are worth spendi ng resources on. More and more companies are coming to terms with the fact that they need to have a data stewardship function in order to be effective in collecting metadata (including definitions, derivations, and data quali ty rules), MDM, and data quality. A lot has been said and spoken about why stewardship is important, but HOW do you do it and be effective with limite d resources (in the "real world")?\nThis seminar details how to s et up a data stewardship function, provide training for your stewards, and run the entire stewardship effort — including managing the Data Stewardship Committee. You'll need help from IT for folks who know the systems and ETL, and this presentation tells you how to coordinate your eff orts, including recruiting help from IT for technical stewards, evaluating and installing Data Governance / Stewardship toolsets, and leveraging an IT sponsor.\nWe will go into considerable detail on what the roles and respon sibilities of the data stewards are, what decisions they have to make, and what processes have to be used in order to make those decisions. In additio n, it covers how to staff projects for stewardship and funnel the informati on from projects back into the overall stewardship process. Communications are another important part of stewardship, and we'll discuss what meeti ngs are needed, what a communications plan looks like, how to report on you r stewardship progress, and how to avoid getting overwhelmed by meetings by leveraging modern collaboration tools.\nYou will learn:\n\n The relationship between data governance and data stewardship\n How to build and staff governance and stewardship organization\n How to recruit stewards and who in the organization is responsible for designating stewards\n What type of person you need in the stewardship role\n What the steward's responsibilities are\n What the stewardship process looks like\n How to break up responsibilities by functional area\n Resources you can use to minimize endless meetings\n What the decision process is\n How to avoid overwhelming stewards when you have a lot of projects\n What and how to document decisions\n A list of Data Stewardship Best Practices\n How to train your stewards to do what they must do\n How to orchestrate a communications plan\n How to build a status report for stewardship and governance\n How to incorporate your stewards into the responsibilities of Information S ecurity\n What the Stewardship maturity model looks like, and how to rank your stewar dship effort\n\nCourse Outline:\n1. Introduction\n\n Current Data Challenges: User, System, Executive, Interpretation, and Manag ing issues\n Getting to an Ideal State: Proper Data Warehousing, Master Data Management, Identity Resolution, Data Quality Improvement, New System Implementation\n \n2. Data Governance — Execution of Authority over Data Manageme nt\n\n Understanding Data Governance: Definitions and Overview\n How to Ensure the Enterprise’s Data Assets are Formally Managed\n Practical Data Governance: Metadata, Data Quality, Policies, and Procedures \n Where Stewardship fits into the overall Data Governance program\n\n3. Data Stewardship — Operational Aspect of Data Governance\n\n Three Main Types of Stewards: Business, Technical, and Project Data Steward s\n Roles of Data Stewards — what they help Determine, Decide, Enforce an d Ensure\n The importance of Data Stewardship\n What Happens Without Data Stewardship?\n\n4. Setting up Your Data Stewardsh ip Organization\n\n Championing Stewardship — Well Executed Data Stewardship Program s\n Keys to Successful Implementation:\n \n Fitting Stewardship into the Data Governance Organization\n Organizing the Stewardship and Creating a Council\n Assigning Responsibilities and Relationships\n Raising Awareness and Communication\n Training Data Stewards\n \n \n\n5. Enterprise Resources — Figuring Out What You’ve Got and Where To Put It\n\n Governing Data: The Information Chain, Source Data Capturing, ETL, Reportin g\n Metadata: Definition, Derivations, Tracking ETL, Supporting Capture and Val idation\n Data Quality — Quality Issues, Documentation, Trouble Tickets, P roject Development\n Tools: Metadata Capture Tools, Data Quality Tools, Stewardship and Governan ce Tools\n Business Glossary: Context, Hierarchy, Terms, Workflow, Statistics\n\n6. Ad justing Methodology — Data Governance Process Integration\n\n Adding Governance To Project Methodology — We are here to help!\n Adjusting Project Methodology:\n \n Working with Project Managers and Project Data Stewards\n Project and Solution Evaluations\n Metadata and Data Quality — Resources, Definitions/Derivations, Validate Rules, Metrics\n Documentation and QA Test Cases\n \n \n\n7. Working With Stewards — Day-To-Day Practical Aspects\n\n Steward Assignment, Duties, and Relationships:\n \n Chief Data Steward — Strategic Leadership\n Enterprise Data Steward — Leading Data Stewards, Program Managem ent, Measurement\n Business Data Stewards — Business Alignment and Management\ n Data Domain Stewards: Alignment and Data Management\n Project Data Stewards: Metadata and Data Quality\n Business, Data Owners, and IT Stewardship\n \n \n Decision Documentation Process and Creating Communication Plan\n Work Flow: Logistics, Working Groups, and Stewardship Council\n Infrastructure Needs and Staffing Requirements\n\n8. Practical Steward ship — Maintaining What We Have Accomplished\n\n Definitions and Derivations — Rationalization, Assignment, Creation, and Approval Process\n Data Quality — Support, Rules, Enforcement, Results\n Reference Data Setup and Repeatable Processes\n Information Security: Classify Data, Document Classifications, User Access, Build Structures\n\n9. Data Stewardship Metrics\n\n Business Results Metrics — Business Value Measurements\n Operational Metrics — Operational Considerations for Effective S tewardship\n Work Progress Reporting\n Critical Success Factors\n\n10. Measuring Maturity and Summary\n\n Stewardship Maturity — Measuring your Progress\n The Data Governance Maturity Model\n Maturity Levels: Initial, Repeatable, Defined, Managed, and Optimized\n Improvement Challenges and Opportunities\n Data Governance Best Practices\n\n DTSTART:20211209T083000 SUMMARY:S1: A Complete Guide To Data Stewardship DTEND:20211209T155959 LOCATION: See Description END:VEVENT END:VCALENDAR