Security / Governance, Risk & Compliance

Data Governance and Data Quality Management

A three-day course on data governance and data quality management — governance frameworks, roles (CDO, data steward, data owner), data quality processes, compliance (GDPR, sector regulations), tools and automation, measuring the maturity of a governance program.

Data governance is not an IT project — it is an organizational program that requires structure, roles and processes

Most organizations have a data problem: duplicates, gaps, inconsistencies between systems, no clear data owners, unclear retention policies. Data governance is the answer — but not a technological one. Governance is first and foremost about organization: who owns the data? Who is responsible for its quality? What are the policies? How do we measure maturity?

Data Governance and Data Quality Management is a three-day EITT training program, delivered on-site or remotely, depending on the participants’ preferences. The program is intended for people with experience in data management — the sessions combine theory with intensive practical exercises.

Who is this training for?

For people building or developing a data governance program in their organization. Especially when:

Your organization is investing in analytics/AI, but the data is of poor quality — you need a governance program as the foundation
You need to ensure compliance with GDPR and sector-specific regulations, but you lack a data management structure
You want to build a business case for investing in data governance and convince the board to fund the program

Three days: from framework to business case

Day 1: Fundamentals — the definition and objectives of governance, frameworks (DAMA-DMBOK, DGI), organizational structure (CDO, data steward, data owner), data catalog and metadata, data policies, design exercises.

Day 2: Quality and compliance — data quality dimensions (ISO 8000), processes (profiling, cleansing, monitoring), tools, GDPR and sector-specific regulations, Master Data Management, data quality assessment exercises.

Day 3: Implementation — business case and ROI, implementation plan (phases, roadmap), technologies, maturity model (CMMI DMM), maintenance and KPIs, business case building exercises.

With over 2,500 trainings in our portfolio, EITT is a trusted partner in competency development. Contact us — we organize closed data governance trainings for teams.

Benefits

Design a data governance organizational structure — roles, councils and an operating model (centralized, federated, hybrid)
Implement data quality management processes — profiling, cleansing, monitoring and quality metrics (ISO 8000)
Create data policies — quality, security, retention and access — that comply with regulations
Ensure compliance with GDPR and sector-specific regulations in the context of data management
Build a business case for a data governance program, with an ROI analysis and the cost of poor data quality
Assess data governance maturity in the organization and plan the development of the program

Who is this training for?

Chief Data Officers and data management leaders building a governance program

Data stewards and data owners responsible for quality in their domains

Data architects designing the enterprise data strategy

Compliance officers dealing with data protection regulations (GDPR, sector-specific regulations)

Business analysts working with enterprise data assets

IT managers responsible for data infrastructure and data quality

Prerequisites

Experience in data management, analytics or business intelligence
Basic knowledge of database concepts and data modeling
Understanding of business processes and data flows in the organization
Knowledge of regulatory requirements related to data management

Training program

Data Governance — definition, objectives (quality, security, compliance, business value), relationship with Data Management (DAMA-DMBOK)
Governance frameworks — DAMA-DMBOK, DGI (Data Governance Institute), operating model (centralized, federated, hybrid)
Organizational structure — roles and responsibilities (CDO, Data Governance Council, data steward, data owner, data custodian)
Data catalog and metadata management — business glossary, metadata repository, lineage, impact analysis
Data policies — data quality policy, data security policy, retention policy, access policy
Exercises: designing a data governance structure for an organization — roles, councils, policies, operating model

Data quality dimensions — completeness, accuracy, consistency, timeliness, uniqueness, integrity (ISO 8000)
Quality management processes — data profiling, data cleansing, matching and deduplication, quality monitoring
Data quality tools — tool overview (Informatica, Talend, Great Expectations), validation automation
Compliance and regulations — GDPR, sector-specific regulations (finance, healthcare), privacy by design, DPIA
Master Data Management (MDM) — golden record, hierarchies, cross-system integration, MDM hub
Exercises: data quality assessment — profiling, problem identification, improvement plan, quality metrics

Building a business case — ROI of data governance, cost of poor data quality, quick wins
Implementation plan — phases (assessment, design, pilot, rollout), roadmap, domain prioritization, change management
Supporting technologies — data catalog tools, data quality platforms, governance automation, AI in governance
Maturity model — CMMI Data Management Maturity, maturity assessment, benchmarking, goals for next stages
Maintenance and improvement — governance program KPIs, board reporting, audits, continuous improvement
Exercises: building a business case and data governance implementation roadmap with ROI analysis

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Training Topics

Frequently asked questions

Is the training technical or business-oriented?

It sits at the intersection of both — it combines the business perspective (strategy, governance, compliance, ROI) with the technical one (data quality tools, data catalog, MDM). Days 1 and 3 are more strategic, while day 2 is more technical. The program is designed for people who need to understand BOTH sides.

Do we cover specific tools?

Yes — day 2 includes an overview of tools (Informatica, Talend, Great Expectations, data catalog tools). We discuss them comparatively in the context of governance, not as separate product courses.

Does the training cover GDPR?

Yes — GDPR is discussed in the context of data governance (privacy by design, DPIA, data retention, data subject rights). However, this is not a GDPR course — we focus on linking compliance with the governance program.

What is the format and duration of the training?

The training lasts 3 days (9:00 AM–4:00 PM) and is available online and on-site. It includes practical workshops — designing a governance structure, assessing data quality and building a business case.

Will I receive a certificate after the training?

Yes, every participant receives a personal certificate of completion issued by EITT.