Security

Data Governance Training – Effective Management of Data Quality and Security

The Data Governance training is an intensive 2–3 day workshop (80% practice, 20% theory) that prepares participants to effectively implement and maintain data governance programs in organizations, especially in the context of increasing use of artificial intelligence.

Duration
6h
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Who it's for

Ideal for teams that…

1 Chief Data Officers and data management leaders, Data Stewards, and Data Owners across business domains
2 Directors, managers, and specialists from companies offering IT services or data-based solutions, including Big Data and AI
3 Data architects and compliance specialists
4 Managers, specialists, and consultants in digital transformation, data analytics, AI, and Data Science
5 Directors, managers, and specialists from IoT device manufacturers, vendors, and service providers handling IoT data
6 Legal counsels, attorneys, and in-house lawyers supporting AI and digital transformation projects
7 Data quality and information security specialists
Outcomes after the program

Application and infrastructure security — a workshop for technical teams.

✓

Define and implement effective Data Governance frameworks and strategies

✓

Build roles and organizational structures that support data management

✓

Achieve and maintain high data quality using tools and metrics

✓

Understand legal requirements and practices ensuring compliance and data security, with deep knowledge of regulations (GDPR, AI Act, Data Act) and their impact on AI and digitalization projects

✓

Master practical skills in managing the data lifecycle, intellectual property, data flows between entities, and protecting the interests of organizations and users

✓

Apply modern technologies for automating monitoring and data management

Program · 3 modules

What we actually do

M01
Day 1: Fundamentals of Data Governance and Legal Frameworks
  • · Definition of Data Governance, goals, and business benefits
  • · Key components and pillars of Data Governance
  • · Chief Data Officer (CDO)
  • · Data Steward
  • · Data Owner
  • · Personal, non-personal, and machine data in governance
  • · Overview of legal regulations on data protection and data sharing
  • · The role of Data Governance in training AI models
  • · Creating data management policies and decision-making processes
  • · Data stewardship, incident handling, and conflict resolution
  • · Assessing organizational maturity
  • · Building Data Governance roadmaps
  • · Ethical principles and human rights in Data Governance
  • · Algorithmic discrimination and AI ethics violation examples
  • · Ethical guidelines and codes
  • · Methodologies for ensuring ethical and legal compliance
M02
Day 2: Data Quality, Compliance, New Regulations, and Intellectual Property
  • · Data quality standards and monitoring
  • · Incident alerting mechanisms
  • · Profiling
  • · Validation
  • · Cleansing
  • · Automation of data quality processes
  • · Integration with data pipelines
  • · Selection and adequacy
  • · Accuracy
  • · Representativeness
  • · Completeness
  • · GDPR
  • · AI Act
  • · Data Act
  • · Compliance management and data security policies
  • · Personal data protection and privacy practices
  • · New obligations for IoT manufacturers and data-based services
  • · User rights: access, portability, and data sharing
  • · Data-sharing agreements and best practices
  • · Copyright protection of works
  • · Public domain and open licenses
  • · Text & Data Mining (TDM) exception for AI
  • · Legal risks related to copyrighted data acquisition
M03
Day 3: Technologies, Implementations, Non-personal Data, and Databases
  • · Automated data discovery and classification tools
  • · Dashboards for data quality and governance monitoring
  • · Integration with analytics, cloud (multi-cloud), and AI platforms
  • · Design
  • · Execution
  • · Maintenance
  • · Building data communities and skills
  • · Data literacy programs
  • · Change management and governance culture
  • · Case studies and group workshops on real datasets
  • · Legal bases
  • · Information duties
  • · Data minimization
  • · Data Protection Impact Assessments (DPIA)
  • · AI-based automated decision-making
  • · Copyright
  • · Sui generis rights
  • · Open Database License
  • · Use and commercialization of non-personal and machine data
  • · Free B2B data flows, agreements, and market practices
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

Ochrona antyspamowa (Cloudflare Turnstile) zostanie aktywowana po wpięciu klucza.

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