Data
Present
IT and Cybersecurity
Distanciel
Data Training
Customized training
Practical Data Quality Training
Improve your understanding of key concepts and operationalize your data quality management
Key information
Prerequisites
- Good general knowledge of information systems and their architectures
- First experience in a Data Management topic
- Experienced audience > 3 years of experience
Target audience
- Data steward
- Data analyst / Data Quality Analyst
- Data cell members / Data officer
- Data owner
- Business IT manager
- AMOA
Educational objectives
- Understand key data quality concepts
- Know how to implement methods and best practices from reference books (DMBOK, Ten Steps to Quality Data and Trusted Information, ...) and our field experiences to:
- Measure and monitor data quality
- Identify root causes of quality issues
- Improve data quality
- Acquire practical skills through case studies and tool-based illustrations (with Informatica, Power BI, and Knime).
Training description
A cornerstone of Data Management, quality control of data is a mandatory step to consider them as an asset. Where to start? How to measure data quality? What processes and tools should be deployed?
Educational and technical means
Educational means
Educational processes
- Training with theoretical contributions
- Practical cases
- Exchanges on the contexts of trainees and feedback from consultant trainers
Evaluation methods
- N/A
Technical means
In-person
- Equipped training room
- Provision of supplies for trainees
Remote
- Access to training via Microsoft Teams
Supervision means
- Data Management expert consultants (at least Senior Consultant grade)
- CDMP certified and members of the DAMA France association
- Bilingual English trainers for English-speaking audiences