Organizations are creating and capturing more data than ever. Creating and capturing data though is just the starting point. Organizations need to leverage that data to drive better outcomes. Most organizations use brute force to manage this data, which is both time-consuming and costly. IT needs to manage this data better. Better management means improved protection, access, and provisioning. At VeeamON 2018 Veeam laid out five steps to intelligent data management to which every organization should pay attention.
Step 1 – The first step to intelligent data management is back up. While it seems like the most obvious first step, most organizations are still in and are in fact stuck in this step. Organizations need to find data protection solutions that can backup frequently. A clean backup every 15 minutes should be table stakes in 2018. The ability to recover that data in about that same 15 minutes should also be a requirement.
Step 2 – The next step in intelligent data management is to aggregate the organization’s data. Data aggregation is not data consolidation. For performance, data needs to be as close to the application and users as possible. Aggregation is the knowledge of data location, who/what is using that data and where are that data’s copies. It may mean storing all data to a single set of data stores controlled by the data management software.
Step 3 – The third step in this process is visibility, which addresses the next big hurdle, provisioning of data. Provisioning of data is more than just recovering it. It is providing access to virtual copies of data for other use cases. Visibility moves data management from its legacy role of an insurance policy (i.e., backup) to where data can be leveraged to speed innovation. Meeting this requirement means that the data management software can deliver virtual copies of data, track changes to those virtual copies and protect them.
Step 4 – The fourth step is orchestration, making sure that when data is recovered or provisioned, it sets all the configurations correctly so that data is seamlessly accessible. Orchestration also sequences application recovery order to make sure that application dependencies are manageable.
Orchestration is also the first step on the path to intelligent data management that moves from policy-based data management to behavior-based data management. At this point data management becomes proactive.
Step 5 – The final step on the path to intelligent data management is automation. Automation moves beyond just the proactive management of data to situational awareness of data. Essentially automation looks at both internal and external factors and the data management process responds to those conditions. For example, if an external malware detection product picks up a ransomware attack, it signals the data management software to restore any encrypted files and then alert IT to the problem.
Every IT professional knows data is critical but many underestimate just how critical that data is. Organizations can’t operate without data. Recovery is must be instant; data has to be provisioned and then decommissioned on-demand. Data Management needs to anticipate when data is needed and automatically place it where it is wanted. The first step on this journey though is backup and recovery, and it is the foundation that drives the rest of the steps to intelligent data management.