Description

Competitive challenges and the increased need for data transparency require a methodology and data architecture that is controlled and aligned with the businesses. This seminar will present the issues and methods for engaging all information systems in this approach.

Who is this training for ?

For whom ?

Anyone having to implement a company data governance approach and/or a Master Data Management project.

Prerequisites

Training objectives

Understand the strategic role of data management for the company.

Understand the principles of data architecture

Implement a governance method

Integrate Master Data management into the approach

Know how to identify MDM players and their positioning

Training program

• Introduction
  • Strategic issues of data for the company.
  • Definition of the notions "Data" and "Information".
  • The different sources of data of the company.
  • The different forms of data exploitation.
  • Operational and decision-making information system.
  • Architectures: Relational / Big Data.
  • Exchanges Exchanges on the strategic role of data for the company.
• Data governance
  • Definition and challenges of data governance.
  • The Cobit approach in data governance.
  • The actors of data governance.
  • The main principles of the data governance approach.
  • References and state of the art.
  • ExchangesrnAn organization implements a data governance approach when merging its IS with a new IS resulting from an acquisition.
  • Study of the impact on the organization and IT
• Le Master Data Management
  • Positioning of Master Data Management in the corporate information system.
  • The essential stages of the Master Data Management approach.
  • Presentation of Master Data architectures Management.
  • Administration of master data.
  • Audit and management of data quality.
  • Synthesis of good practices.
  • The role of users in the MDM system.
  • Collective reflection Case study of an information system without Master Data management on which a needs analysis is carried out in MD.
  • Comparison of 2 possible implementation approaches.
• Data lifecycle
  • Typology and Data Volume.
  • Database Archiving.
  • Data Confidentiality.
  • Test Data Management.
  • Decommissioning of applications.
  • Exchanges Exchanges on data management and their life cycle.
• Presentation of MDM offers
  • Market trends MDM in Informatica / IBM / SAP suites.
  • MDM Microsoft.
  • Talend MDM.
  • Conclusion.
  • Exchanges Exchanges on possible approach strategies depending on the context.