I recently attended the ARMA International conference in Chicago, Illinois. The event showcases the latest information management and governance solutions, and highlights the needs for electronic records and content management, cloud computing, social media concerns, and more.
At the event, my colleagues and I presented some of our solutions and noticed that we were receiving a lot of feedback from companies that were transferring segments of data or all of their electronic data to cloud systems.
In doing so, I observed that moving data to the cloud is not as simple as solely migrating information. Most companies are cleaning up, organizing and optimizing their data as a part of their data relocation efforts. In the past, they would simply add more storage to accommodate extra data. In cleaning files up first, however, they take advantage of an ideal time to consolidate information and make sense of their information chaos.
Data cleaning before the mover’s arrive
There are a few reasons to clean up data before transferring it to a cloud platform.
- First, many companies have never had the opportunity to take inventory of or organize their files. Prior to moving it, that’s the ideal time to reorganize the information. Then the organization has a fresh start when they begin using the cloud to store and access data.
- When an organization migrates their data to a cloud, they will pay depending on how much storage space they need. Why migrate everything when you could be paying to move useless files? This is another reason why companies choose to clean up their data before transferring it to the cloud.
- Finally, organizations are reclassifying data before moving it to the cloud to lower the risk associated with critical information. This is a pivotal move to ensure companies stay in compliance with governing regulations and safeguard at-risk data.
How to classify data before moving it to the cloud
In migrating data to a cloud system, information is typically classified into categories such as business-critical files, risk-based content and point-in-time business value information. The first two are self-explanatory, but the term “point-in-time” refers to data that is needed at a certain time. For example, a health clinic may need a patient’s records while they are being treated for a condition or referred to a specialist; after treatment, though, the record isn’t as relevant or in demand.
I’ve seen quite a trend of data reclassification prior to cloud migration in the financial and life sciences sectors, but other fields are also capitalizing on this solution in order to reduce their carbon footprints. Some companies move one aspect of their data to the cloud at first, then wind up migrating more to the cloud.
In a perfect world, companies could just reboot their data systems and have applicable information in all the right places. There’s no one-click approach for this, however, which is why data cleaning prior to cloud implementation is an effective way to reorder information, purge unneeded data and more easily access files.
What did your organization do with data before moving it to the cloud?