This paper assesses the current business landscape and identifies the challenges faced by the enterprises in the data management domain. It proposes an ‘IDEAL’ approach:
- Identify the need and stakeholders- enterprises have multiple data management needs across the data lifecycle. Thus, deciding what needs to be managed is very critical for any organization.
- Define the scope, landscape and governance model-Organizations are recommended to first define processes, business functions, data and systems involved. Next, enterprises should define and socialize governance model.
- Establish the metadata blueprint and governance body- process and technology levers of the solution are implemented in the organization
- Analyze the metrics, leveraging reports and analytics to monitor deviation-data governance body should continuously monitor defined metrics on a regular basis to ensure defined priorities are progressing as per the plan
- Liaise with stakeholders- data governance body is provided with extensive communication methods to liaise effectively within the organization and enable tracking of status of communication
Thus, metadata driven data governance is a powerful tool for governance teams who can derive intelligence and monitor metrics to ensure right analysis of data assets.
Learn how metadata driven data governance helps organizations build cost effective, scalable and high performance systems.