NEVADA | PROFESSIONAL EXPERIENCE

Program Professional Framework

Big Data Governance: Bad Data or Better Data or Best Data

Program Overview

Large data platforms quickly turn into data swamps when ownership, quality rules and metadata are missing. This programme shows how to move from bad to better to best data through governance designed for big data environments: operating models with owners and stewards, policies and standards, data quality dimensions and measurement, metadata catalogues and lineage, master and reference data, classification, privacy and access control, and alignment with DAMA-DMBOK and national data management frameworks such as those issued by the Saudi National Data Management Office.

Learning Outcomes

✓Design a data governance operating model with councils, owners and stewards and clear decision rights.
✓Draft data policies and standards covering quality, classification, retention and access.
✓Measure data quality across dimensions such as completeness, accuracy, timeliness and consistency.
✓Specify metadata catalogue and lineage requirements for a data lake or lakehouse.
✓Apply data classification and privacy controls to sensitive and personal datasets.
✓Build a phased governance maturity roadmap with measurable milestones.

Target Audience

Chief data officers and data governance leads
Data stewards and data quality analysts
Data architects and platform owners
Compliance and privacy officers

Detailed Program Modules

01Why Big Data Needs Governance

Characteristics of big data environments
From bad to better to best data
Cost of poor data quality

02Governance Operating Model

Councils, owners and stewards
Decision rights and escalation
DAMA-DMBOK and national frameworks

03Policies and Standards

Data policy hierarchy
Classification and retention rules
Data sharing agreements

04Data Quality Management

Quality dimensions and rules
Profiling and monitoring at scale
Issue management and remediation

05Metadata, Lineage and Master Data

Business glossaries and data catalogues
Lineage across pipelines
Master and reference data management

06Security, Privacy and Maturity

Access control and privacy controls
Governance metrics and scorecards
Maturity assessment and roadmap

Training Methodology

Interactive expert-led sessions grounded in workplace examples

Case studies and practical exercises drawn from the region

Group workshops with peer review of decisions and deliverables

Formative feedback against clear performance criteria

Applied Project & Assessment

Applied Project

Participants develop a governance plan for a big data platform in a Gulf entity: operating model chart, three core policies, a data quality scorecard for one critical domain, catalogue and lineage requirements and a maturity roadmap.

Assessment

Short diagnostic at the start, practical tasks linked to each learning outcome, and evaluation of the applied project against published criteria.

University Certificate & International Accreditation

Professional Certificate accredited by Twintech International University College of Technology in Big Data Governance: Bad Data or Better Data or Best Data

International accreditation: American Association of Innovation (AAI)