Introduction to Data Management - IDM

Discipline: Multi-Discipline Training / Petroleum Data Management
Level: Basic
Instructors who teach this course:

  • About the course
  • Designed For
  • You will learn
  • Course Content
This course provides an overview of data management in E&P, focusing on the subsurface domain. The need to deliver good data management is increasingly being seen as providing competitive advantage across the E&P industry, since wise business decisions depend on sound data and information. Participants will leave this course with an understanding of the core E&P data types, their use in the business, and data management issues and challenges facing companies. You will have the knowledge and tools necessary to participate in developing a structured data management framework, which will deal with these issues in a practical and effective manner to ensure business efficiency and value is realized. This course provides an understanding of essential E&P data management principles and concepts using an interactive classroom format; participants will have the opportunity to learn from presentations, exercises, and interactive discussions. Course instructors are experienced data management practitioners, who have delivered services and projects to many E&P companies, from small independents to super majors.
As this course is foundational it will be of most benefit to those with little or basic prior understanding of technical data used in the E&P industry. Course attendees may hold a variety of roles such as data or information managers, technical managers and assistants, technologists, geologists, geophysicists, etc.
  • What is data management, why it is important, understanding of data as an asset, its lifecycle, benefits of good data management, and its potential value
  • The core data types in the E&P industry and valuable best practices for them
  • Common data management issues and challenges, and the impact on the business
  • The important components of a data management framework
  • How to map issues onto a data management framework
  • Data types: definitions
  • Common data management issues: causes of data issues, data management best practices, business impact
  • Overview of data management: definition, data lifecycle, importance and value of data management, benefits of good data management, business case aspects and barriers
  • Data management framework: governance, architecture, security, reference and master data management, data quality management