Subscribe to DSC Newsletter

What is Information System Governance?

The objective of IT governance is to maximize the added value of IT to the company strategy in its definition as well as in its application. It means it leads the developments, the implementation and the use of IT. According to the governance experts it has to be pre-schedule, planned, transparent, fair and efficient. Thus it is important to:

Organize a governance structure (setting up of a department including stakeholder’s representatives and an executive in charge of the governance).

Define processes (governance planning and organization of about ten key processes such as budget, services billing, demand management, project portfolio management, service level agreements (SLA), human resources...).

Set up goals and way to measure them on the following points: creation of value, risks, compliance, processes efficiency and financial aspects.

Business Intelligence Governance Specificity

The governance of Business Intelligence projects has to take into account the specificity of the study, the implementation and the use of BI systems. For instance, in most Business Intelligence projects users have challenges to supply detailed specification of their needs and have to pass through learning stages which imply the system being built slowly and in an iterative way. Besides, the BI projects are firstly centered on the integration of data coming from diverse applications, and this stage is always at the start of data quality problem discovery. To face efficiently this situation, a good governance system is necessary in order to organize dialogues between the different departments of the company and the IT department.

The BI Governance specialists recommend focusing the efforts on the following points:

  • The governance management structure: to have a board of directors representative, to choose carefully the persons involved, to define a governance charter.
  • The governance mission statement: to take into account the company strategy, organization, and culture and to define principles, policy and members objectives.
  • The demand portfolio management: to organize the business opportunity identification, define criteria to measure and rank the results, audit systematically the systems three years after their development.
  • The data governance: to create a surveillance committee, define the data administrators, define data management policies and processes, set up norms and procedures for the data use, do the checking and controls.
  • The services level agreement (SLA): to involve every SLA development stakeholders, establish rules to work together, define and execute the SLA
  • Stakeholder’s management: to involve all the stakeholders as soon as possible, define communication and teaching plans.


To go further look at the Teradata view on this subject:


Views: 367


You need to be a member of Data Science Central to add comments!

Join Data Science Central

© 2021   TechTarget, Inc.   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service