An organization with its eye on cloud integration often begins with archiving cold data. According to IBM, 90 percent of the data accessed is less than one year old, so companies are highly motivated to remove the weight of cold data and move it to a cloud storage solution.
The drawback of such a process is that it can be time-consuming, requiring the IT department to schedule the migration of archives during off-hours to avoid disrupting the continuity of business processes. A migration of archives is also conducted using slow Internet bandwidth, causing the process to take even more time.
There’s another problem that accompanies the archiving of cold data to cloud storage solutions. While most data needed is current, there’s still that 10 percent or so that needs to be retrieved from the archives. Organizations must weigh the cost of retrieving the data with the savings of using a cloud-based storage solution.
The Benefits of Using a Metadata Engine for Cloud Integration
These problems can be solved using a metadata engine to archive cold data. The metadata engine adds a cloud tier to the IT structure and allows the metadata engine to automatically load balance the cold data, in accordance with the policy set by your IT administrators. Your team can set parameters to automatically archive any data that has not been accessed for 30, 60 or 90 days, as you determine the timeframe that best fits your processes.
A metadata engine is also intuitive in the ways it archives data. It will automatically archive data that is not being used, but it also moves that data at a time when it will have no impact on running applications.
One of the biggest challenges for archiving cold data is weighing the possible cost of retrieving that data if it’s needed. IT departments are often forced to scramble to get to the necessary files and must weigh the cost of retrieving the data with the need to use it. A metadata engine keeps the archives accessible, but it also allows for the pulling of single files, which reduces bandwidth costs of retrieval. In addition, administrators can determine whether the archived file includes images or video, which can increase bandwidth costs of retrieval.
While a metadata engine can’t solve every cloud integration challenge, it certainly addresses many of the problems that come with archiving cold data. To find out more talk to our team at Cloud Source. We can help you weigh your archiving options and choose the solution that is most efficient and cost-effective for your organization.