Shed Light on Dark and Cold Data
Posted in tech
Few people today would doubt the immense value of data in our modern economy. Yet, many IT teams are sitting on “dark data,” which market research company Gartner Inc. describes as "information assets that organizations collect, process and store in the course of their regular business activity, but generally fail to use for other purposes."
Typically, dark data is data that enterprises are ignorant of – they don’t realize they have it, or how it’s being used. Some examples of dark data include:
- Data that might put an organization at risk. For example, social security numbers might be stored on an unencrypted storage volume.
- Data that has value, but that the organization isn’t actively using. For example, it might be data that can provide real insights, but that isn’t being analyzed by the organization’s BI or data warehousing application.
- Data that has served its purpose and is no longer needed, and is therefore unnecessarily consuming primary storage capacity.
In addition to sitting idle and even potentially putting the business at risk, dark data also adds storage costs. If the data had value and could be put to work to extract that value, it could be serving the enterprise as an asset, rather than just eating up capacity as an expense.
DataSphere gives enterprises visibility into how their data is being used, including dark data and cold data. This visibility provides unprecedented insight into what was previously hidden from IT. By analyzing metadata, DataSphere assesses a number of data attributes, then automatically and transparently moves data to the ideal storage device to align with IT’s policies for performance and price.
This policy-driven data management enables IT to reduce organizational risk. By creating a volume group comprised of only encrypted volumes, IT can ensure data is always placed on encrypted stores. Placing policies on sensitive data ensures that data assigned those policies only gets placed on the encrypted volumes.
Similarly, data that is no longer being accessed can be archived to low cost NAS, object, or public cloud storage, freeing valuable primary storage capacity for applications that need it. In addition, since DataSphere eliminates storage silos, dark data can be made visible to IT so it can become accessible to business intelligence applications, maximizing the amount of data that can be mined for critical insights.
Putting Cold Data on Ice
A close cousin of dark data, cold data is data that is rarely or never accessed. Due to data mining, big data, and analytics opportunities, enterprises today rarely delete even cold data. In the case of data required for regulatory compliance, this retention can be a business requirement, and a costly one at that. As the volume of data enterprises store is continually increasing, it’s now vital for organizations to archive this data to lower cost resources to keep costs in check.
DataSphere enables enterprises to automate the tiering of cold data to appropriate resources. Data under regulatory compliance can be automatically and transparently moved to on-premises filers or object stores that meet data’s protection requirements. Importantly, this data can be automatically retrieved should it be needed again (for example, in the event of an audit), without the need to modify applications to use object storage. DataSphere can also move cold data that may never be needed again to even more cost-effective stores, such as a public cloud.
As enterprise IT continues to deal with an ever-increasing inundation of data, it’s vital that we find a way to identify cold data: data this is no longer being accessed, as well as dark data: data that might be useful, but that organizations don't even know they have. DataSphere gives enterprises the insight they need to see what has been hidden, and automatically moves data to the ideal storage to meet IT requirements for managing these datasets. Want to learn more about how DataSphere can automate your cold and dark data management? Connect with us at firstname.lastname@example.org to schedule a meeting or demo.