Session 1: Data Governance & Data Management – Definition and Importance

•  The Definition of Data Governance, Data Management; how they differ from Information Technology (IT)
• The key role of data governance – why is it important
• What data is required and why?
• Why most firms are launching “enterprise” data programs
• So many “data” terms in the marketplace; the basic “definitions” and what you need to know (e.g. Big Data, Master Data, Data Lineage, Data Profiling, Data Transformation, Metadata, Data Science, Data Architecture, Key Data Indicators, and many more.)

Case Study/Examples: how major firms are embracing Data Governance, Data Management Framework

Session 2: Data Governance – Organisation; Basic Functions; Roles & Responsibilities

•  Major components of a typical Enterprise Data Governance Program
• How Data Governance is typically aligned and managed organizationally
• Basic functions performed by Data Governance
• Major roles and responsibilities (e.g. Chief Data Officer (CDO); Head of Data Governance; Data Owners, Data Stewards and Data Custodians)

Session 3: Key Concepts of Data Management 1

•  Typical responsibilities of Data Management defined
• Data Standards – Measuring and monitoring compliance
• Data Quality – How data quality improvement is achieved, measured, reported
• Data Remediation – Data consistency, data cleansing; data expectations and tracking results
• Issue Management & Resolution

Case Study/Example: The basics of setting up an issue tracking process

Case Study/Example: Reporting on resolution

Session 4: Concepts of Data Management 2

•  Data Lineage – Defined; why it is so important to understand, a basic example
• Metadata Management – A simple definition; how it is implemented and why
• How Data Management progress/issues/results are reported to Management the Board and other stakeholders.

Discussion: what really matters to the board and senior management?

Session 5: Changing Expectations and Data Impacts

•  Overview of the most significant regulations that necessitate Data Governance
• ESG and data management
• The data products and their impact on data governance
• The impact of operational resilience on data management
• Stakeholder expectations regarding data
• Critical, sensitive an public data

Exercise: What are the critical elements of your firm’s ESG policy and data compliance programme?

Session 6: Implementing Data Management and Governance

•  Ensuring proper organisational alignment, commitment, resources
• The comprehensive Current State Assessment
• 3rd Party Assessment Methodologies
• What is needed to maintain an effective programme

Discussion : What are most critical challenges when implementing a Data Governance programme

Exercise: draft an ineffective implementation of a data management and governance programme

Session 7: The Future

•  Data products and future expectations
•  The future of data and how this is changing
• The role of ML and AI – how will this change data products?Session 8: Summary, discussion, and Q&A

Delegates will gain specialist technical and behavioural knowledge, techniques and approaches, I dusted products and practical applications, and will specifically specifically

• Gain an understanding of the key concepts and overall objectives of Data Governance and the imperative for establishing firm-wide data governance programs/organisations.
• Be conversant with the basic terminology used when discussing Data Management/Data Governance, the major functions, typical roles and responsibilities.
• Appreciate the key issues that relate to data governance and the approaches to be adopted

Highly interactive expert-led intensive presentation, Q&A, group real-time in-depth case studies, regulation and discussion supported by key principles and theory. The virtual learning platform uses safe, industry preferred encrypted Cisco WebEx to optimize live face-to-face visual interaction, discrete chat, for polling and quizzes.

(An invitation via email with access link is included for all participants.)