Course : Data governance: understanding and practicing
Practical course - 3d
- 21h00 - Ref. GDD
|
Download in PDF format
Share this course by email
 | Understanding data governance |
| Understand the many players involved in data: challenges, roles, responsibilities, profiles and activities within processes |
| Understand the different possible organizations |
| Aligning business, IT and data challenges |
| Implement data governance to manage data as assets |
| Develop a data governance culture within your organization |
Intended audience
Anyone interested in setting up an organization and processes around data.
Prerequisites
General knowledge of information systems or data-related fields (MDM, data architect, modeler, data engineer, business/data analyst....)
Practical details
Teaching methods
Active
Course schedule
1 Introduction
- Defining data governance
- Role and scope: knowledge of assets, regulations and quality
- Strategic issues for the company and the ROI of governance
- Governance models: centralized, federated, decentralized
- Data governance within the information system and for AI: data/IT/IA governance
- Governance within data management
- Managing data as assets: the impact of big data and personal data regulations on data asset management
Case study
Presentation of the historical players in the information system managing data and recruitment of a new player for personal data. Group discussion.
2 Data governance at the heart of data management
- Defining the data life cycle
- Definition of data management and its areas of expertise
- DAMA presentation "Body of Knowledge"
- Data architecture, modeling, data mesh
- Quality
- Master data management - managing data repositories
- Asset knowledge and management
- Safety and regulations
- Data storage and retrieval
- Data maturity framework
Case study
Case studies: security and regulations at the heart of governance project start-ups, assessment of an organization's data maturity. Exchange on the impact of Big Data on DAMA usage.
3 The new players: CDOs and data governance officers
- Chief data officers: profiles, roles, responsibilities, positioning within the organization
- Data governance and data asset managers
- Players driving the transformation of data organization
- Creation of a data office and choice of organization (centralization or not)
Case study
Recruit a CDO and establish his or her position within a company.
4 A governance framework for orientation
- Presentation of a generic data governance framework
- Overview of players, their roles and responsibilities
- Heritage knowledge and data catalog creation
- Definition of data lineage
- Regulations and contacts with regulatory authorities
- Ethical usage, a trusted and responsible player
- Business management of data access, confidentiality and security
- Quality
- Setting up a committee structure
- Training and acculturation to promote a data culture
Case study
Supporting the Data Governance Officer in his or her first few months.
5 At the heart of heritage knowledge, business objects and modeling
- An organized and consistent terminology to describe data assets
- Structured and unstructured data
- Thesaurus, glossary, business dictionary and data modeling
- Ontologies and models: viewing, understanding and sharing a data set
- Data and metadata: definitions, standards and conventions
- Governance, enterprise architecture and data architecture
- Link between technical and business vision
Case study
Design of the data collection process and modeling for heritage knowledge.
6 Data governance processes
- Interactions between data players within and outside projects
- Management of confidential and retention data, uses, knowledge of data assets in projects, modifications to data from sources
- Data quality management processes at data acquisition: actors and quality flows
Case study
Launch of a governance project based on heritage knowledge.
7 The data transformation toolbox
- Data governance and organizational transformation
- Tools for transformation
- An ACTES model: strategic alignment, knowledge of assets and business model, business transformation, stakeholder commitment, security and regulation
- Data culture and data community management: levers for transformation
Storyboarding workshops
Start with the first actions for your context.
PARTICIPANTS
Anyone interested in setting up an organization and processes around data.
PREREQUISITES
General knowledge of information systems or data-related fields (MDM, data architect, modeler, data engineer, business/data analyst....)
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
Anyone interested in setting up an organization and processes around data.
PREREQUISITES
General knowledge of information systems or data-related fields (MDM, data architect, modeler, data engineer, business/data analyst....)
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TEACHING AIDS AND TECHNICAL RESOURCES
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
Dates and locations
Dernières places
Date garantie en présentiel ou à distance
Session garantie