Welcome! GovernYourData.com is an open peer-to-peer community of data governance practitioners, evangelists, thought leaders, bloggers, analysts and vendors.
The goal of this community is to share best practices, methodologies, frameworks, education, and other tools to help data governance leaders succeed in their efforts.
ILM and Data Governance
Information Lifecycle Management (ILM) is a process and set of strategies that align IT investments with information value. The result of a properly implemented ILM strategy is lowered total cost and improved resource utilization. Organizations who have made ILM an integral component to their data governance initiatives save millions of dollars by eliminating the need for excess IT infrastructure.
When the business and compliance teams can deliver a clear set of requirements for how long data is kept and how easily it needs to be accessible, IT is in a better position to plan for storage and server capacity needs. In one project, our team freed up $13M just by eliminating unused and redundant copies of data. If you are looking for ways to pay for your data governance initiatives, ILM delivers hard dollar savings that can provide the self funding needed to get things started and keep them going.
Spring is just around the corner, anyone interested in kicking off a discussion on data cleanup best practices?
Tags: ILM, data, governance, information, lifecycle, management, retention
Views: 52
Replies to This Discussion
-
Permalink Reply by Richard on -
Hi Julie,
Good idea - nothing like a good spring clean!
Best practices? I'm a bit of a techie, so in my view, best practice should be that you have your data modelled and mapped before you attempt to retire it.
A metadata dictionary is a model of all the data that flows throughout the organisation. One of the key reasons why people are reticent to delete data, is that they don't always know what the impact to the organisation is. You can use your metadata dictionary to ascertain the purpose of your data, and the impact of retiring it.
So for starters, I will volunteer that retiring data is risky without good models that you can query to evaluate impact of deletion.
ATB,
Rich
© 2013 Sponsored and Hosted by INFORMATICA
Powered by
