The Complete Guide to Data Stewardship


Data Governance is crucial to properly using 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 apply to determine data quality, and what data quality issues are worth spending 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 quality 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 limited resources (in the ”real world”)?

This seminar details how to set 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 efforts, including recruiting help from IT for technical stewards, evaluating and installing Data Governance / Stewardship toolsets, and leveraging an IT sponsor.

We will go into considerable detail on what the roles and responsibilities 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 addition, it covers how to staff projects for stewardship and funnel the information from projects back into the overall stewardship process. Communications are another important part of stewardship, and we’ll discuss what meetings are needed, what a communications plan looks like, how to report on your stewardship progress, and how to avoid getting overwhelmed by meetings by leveraging modern collaboration tools.

You Will Learn:

  • The relationship between data governance and data stewardship
  • How to build and staff governance and stewardship organization
  • How to recruit stewards and who in the organization is responsible for designating stewards
  • What type of person you need in the stewardship role
  • What the steward’s responsibilities are
  • What the stewardship process looks like
  • How to break up responsibilities by functional area
  • Resources you can use to minimize endless meetings
  • What the decision process is
  • How to avoid overwhelming stewards when you have a lot of projects
  • What and how to document decisions
  • A list of Data Stewardship Best Practices
  • How to train your stewards to do what they must do
  • How to orchestrate a communications plan
  • How to build a status report for stewardship and governance
  • How to incorporate your stewards into the responsibilities of Information Security
  • What the Stewardship maturity model looks like, and how to rank your stewardship effort

Course Outline:

  1. Introduction
  • Current Data Challenges: User, System, Executive, Interpretation and Managing issues
  • Getting to an Ideal State: Proper Data Warehousing, Master Data Management, Identity Resolution, Data Quality Improvement, New System Implementation
  1. Data Governance – Execution of Authority over Data Management
  • Understanding Data Governance: Definitions and Overview
  • How to Ensure the Enterprise’s Data Assets are Formally Managed
  • Practical Data Governance: Metadata, Data Quality, Policies and Procedures
  • Where Stewardship fits into the overall Data Governance program
  1. Data Stewardship – Operational Aspect of Data Governance
  • Three Main Types of Stewards: Business, Technical and Project Data Stewards
  • Roles of Data Stewards – what they help Determine, Decide, Enforce and Ensure
  • The importance of Data Stewardship
  • What Happens Without Data Stewardship?
  1. Setting up Your Data Stewardship Organization
  • Championing Stewardship – Well Executed Data Stewardship Programs
  • Keys to Successful Implementation:
    • Fitting Stewardship into the Data Governance Organization
    • Organizing the Stewardship & Creating a Council
    • Assigning Responsibilities & Relationships
    • Raising Awareness & Communication
    • Training Data Stewards
  1. Enterprise Resources – Figuring Out What You’ve Got and Where To Put It
  • Governing Data: The Information Chain, Source Data Capturing, ETL, Reporting
  • Metadata: Definition, Derivations, Tracking ETL, Supporting Capture and Validation
  • Data Quality – Quality Issues, Documentation, Trouble Tickets, Project Development
  • Tools: Metadata Capture Tools, Data Quality Tools, Stewardship and Governance Tools
  • Business Glossary: Context, Hierarchy, Terms, Workflow, Statistics
  1. Adjusting Methodology – Data Governance Process Integration
  • Adding Governance To Project Methodology – We are here to help!
  • Adjusting Project Methodology:
    • Working with Project Managers & Project Data Stewards
    • Project and Solution Evaluations
    • Metadata and Data Quality – Resources, Definitions/Derivations, Validate Rules, Metrics
    • Documentation and QA Test Cases
  1. Working With Stewards – Day-To-Day Practical Aspects
  • Steward Assignment, Duties and Relationships:
    • Chief Data Steward – Strategic Leadership
    • Enterprise Data Steward – Leading Data Stewards, Program Management, Measurement
    • Business Data Stewards– Business Alignment & Management
    • Data Domain Stewards: Alignment & Data Management
    • Project Data Stewards: Metadata and Data Quality
    • Business, Data Owners and IT Stewardship
  • Decision Documentation Process & Creating Communication Plan
  • Work Flow: Logistics, Working Groups and Stewardship Council
  • Infrastructure Needs & Staffing Requirements
  1. Practical Stewardship – Maintaining What We Have Accomplished
  • Definitions & Derivations – Rationalization, Assignment, Creation and Approval Process
  • Data Quality – Support, Rules, Enforcement, Results
  • Reference Data Setup & Repeatable Processes
  • Information Security: Classify Data, Document Classifications, User Access, Build Structures
  1. Data Stewardship Metrics
  • Business Results Metrics – Business Value Measurements
  • Operational Metrics – Operational Considerations for Effective Stewardship
  • Work Progress Reporting
  • Critical Success Factors
  1. Measuring Maturity and Summary
  • Stewardship Maturity – Measuring your Progress
  • The Data Governance Maturity Model
  • Maturity Levels: Initial, Repeatable, Defined, Managed and Optimized
  • Improvement Challenges and Opportunities
  • Data Governance Best Practices


Data Stewardship: A Complete Guide

Detailed outline for 4 afternoon presentations 

Day 1

    • The challenges of managing your data
    • What governed data enables you to do
    • Understanding Data Governance
    • The relationship between Data Governance and Data Stewardship
    • Understanding Data Stewardship
    • Goals of Data Stewardship
    • Defining “governed data”
    • What drives governing your data?
    • What are the main and ancillary types of Data Stewards?
    • What is a Business Data Steward?
    • Characteristics and Benefits of being a Business Data Steward
    • Authority and Accountability of Business Data Stewards
    • The structure of a Data Governance Organization
    • The responsibilities of each group in Data Governance
    • Understanding the role of the Business Data Steward
    • Understanding the role of the Data Governance Program Office
    • Understanding the role of Data Governance IT Support
    • Operational Data Stewards and their role

Day 2

    • The Data Governance Operating Model
    • Data Governance Program Office key personnel
    • An Outline for Implementation
      • Being a champion of Data Stewardship
      • Communications and the message
      • Support from Above and Below
      • Understanding the Organization
      • Assignment of Responsibilities
      • Processes and Tools
    • Figuring out what you’ve got: Metadata, Data Quality, Processes, and Tools
    • Training the Data Stewards – a detailed outline for complete training
    • Understanding the disconnect between producers and users of data
    • Adding Data Governance to Project Methodology
      • Why add Data Governance and Stewardship to Project Methodology?
      • Data Stewardship tasks that should be part of a project
      • Using a template to define each task
      • Embedding the tasks in a project tool
      • Process Integration
      • Working with and training the Project Managers
      • The value of Data Governance to a project
      • How to use a “hybrid” model for project support
      • The duties of a Project Data Steward
      • Important aspects of a project for Data Stewards: Initial evaluation, metadata, data quality, design approvals, solution evaluation, and test cases.

Day 3

    • Tools for Data Stewardship
      • Data Governance Web Site
      • Wiki
      • Business Glossary
      • Issue Log
      • Data Profiling Tool
      • Metadata Repository
      • Building and using workflows
    • Communication Plan
    • Data Governance Roadmap
    • Practical Data Stewardship
      • Key Data Elements
      • Assignment of Business Data Stewards
      • Building robust business definitions and derivations
      • Instituting repeatable processes
      • Working together (logistics)
      • Documentation and Communication
      • Options for implementation of Data Stewardship

Day 4

    • Data Steward roles in Enterprise efforts
      • Data Quality
      • Reference Data
      • Master Data Management
      • Information Security
      • Data Lineage
      • Process Risk Management
    • Data Stewardship Metrics
      • Business Results
      • Operational Results
    • Data Stewardship Program Maturity Measurements
      • Defining the dimensions
      • Identifying the levels
      • Building and using the Maturity Grid
+ Lue koko esittely


David Plotkin

David Plotkin is the Director of Metadata Services at a large financial services institution, directing metadata activity in support of data management, including implementing data governance and data stewardship in applications such as Collibra Data Governance Center. He is also responsible for creation of metadata quality standards, enforcement of business rules through the use of workflows and coordination of personnel across the enterprise, and communication of metadata protocols.

He has been working with data governance, data modeling, metadata and data quality for nearly 30 years. He is a popular speaker at DAMA chapters and conferences, and serves as a subject matter expert on many topics around metadata, data governance, business rules, and data quality. He also is the author of the book “Data Stewardship, an actionable guide to effective Data Management and Data Governance” (2nd edition).

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The Complete Guide to Data Stewardship

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David Plotkin
4 iltapäivää
Etäkoulutus 14-18.00
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