Data Governance and AI
Why Governance Matters
Data Governance and AI –
Two-Way Street
Legal Eagles and Regulators
Government is Coming for your AI
Operating Model for Success
What will make it work
AI Governance
Process
Develop, Review and Finalize Data Policies, Standards, and Procedures against best practice
People
Establish or Assess Data Governance Organization including roles and responsibilities
Data Governance
I.e.. NPI, Sales Orders, Product Rationalization, etc.
I.e. Executive Sponsors, Data Stewards, etc.
Technology
Leverage tools to help automate and monitor data quality and Metadata Management
Culture
Crafting a corporate culture that ensures data remains central to all roles
I.e.. HR, Legal policies, Procurement, Maturity etc.
I.e. Data Catalogue, Business Glossary, Data Lineage, Data Observability, Data Quality etc.
Taking Data Governance from Theory to Practice
The Data Governance Map provides practical step-by-step implementation guidance for effective rollout of Data Ownership and Data Utilization within the company.
Principles and guidelines for Data Owners and Data Users
• The Data Governance Operating Model provides practical step-by-step implementation guidance for effective rollout of Data Ownership and Data Utilization within the company
• It is an implementation support document primarily aimed towards Data Owners and Data Users helping them to effectively fulfil their accountabilities
• Each Data Owner and Data User has a group of supporting stakeholders (e.g. Data Steward, Data Analyst, BA) helping them in executing each implementation step effectively
AI and Data Governance Roadmap Approach Agile Iterations
Optimising Processes
Establish review and improvement
Cycles for all aspects of Data work
Catalog and Lineage
Build on Catalog and build the foundations for Lineage
Data Literacy
Establish an engagement program that uplifts Corp stakeholders
Documentation
Describe Data, Describe Process, Describe Methodology etc…
AI Automation
Identify opportunities for increased governance and process automation
AI Traceability
Establish a governed enterprise-wide solution
Executive Sponsorship
Build a Data First organisation from the top
Initial Governance Assessment and MVP Planning
Engage to discover the scope and objectives
Take a small number of weeks to deep-dive into your: Existing governance AI roadmap and capabilities Business Objectives
Find the Business Use Case to focus the MVP on
Build a backlog around that roadmap
Define the Operating Model objectives
Kick off the implementation
Data Governance
People
Establish or Assess Data Governance
Organization including roles and responsibilities
I.e. Executive Sponsors, Data Stewards, etc.
Data Governance
Technology
Leverage tools to help automate and monitor data quality and Metadata Management
I.e. Data Catalogue, Business Glossary, Data Lineage, Data Observability, Data Quality etc.
Process
Develop, Review and Finalize Data Policies, Standards, and Procedures against best practice
I.e.. NPI, Sales Orders, Product Rationalization, etc.
Culture
Crafting a corporate culture that ensures data remains central to all roles
I.e.. HR, Legal policies, Procurement, Maturity etc.
Want to Know More?
Watch the On-demand webinar on Data Governance & AI
