Let’s say you’re getting ready to retire from government. During your lifelong career, likely many government agencies managed your data — everything from your basic name, social security number, job title, pay and even your project information and background investigations. But when you retire, an oversight agency takes over to manage your retirement benefits, and then the challenge is this: How do you bring together all of your information? Over your career everything was kept in separate, unconnected systems, and now you and the oversight agency have a problem.
It doesn’t have to be that way – not if your data is managed holistically as an organization from the outset.
Government agencies today understand that data is the beating heart of their organizations. Just like managing your heart health leads to a better life, managing data holistically means you’re in good shape for the long run.
Holistic data management not only allows agencies to know where all their data is, but it’s also much easier to securely manage that data. This approach also enables effective data governance and mitigates compliance challenges, as well as storage issues.
Holistic data management also allows organizations to use newer technologies, like advanced analytics, artificial intelligence and the Internet of Things. These capabilities are critical today, because they can help agencies prepare for the unexpected.
So, how can you move toward holistic data management?
You can’t move what you can’t see or don’t know about, so take the time to map what data you have, where it is stored, and who has access to it. You have to get visibility as an enterprise and not as the distinct business units that collect the data. The more you understand the information you have, the better.
Then, once you know what you have, you can begin to assess and map out a transition to a multi-cloud environment making sure that you automatically build an index of your data. By taking the steps of indexing while backing up, you build resilience for recovery, security and compliance while creating your backup copies. Holistic data management requires building an index while you begin automating your data management processes.
Here are three best practices for implementing a holistic approach to data management:
First, embrace automation whenever possible.
Would you spend time vacuuming your floors if somebody gave you a Roomba? Probably not. The same is true with data management.
Manual processes like scheduling backups or moving data to an archive take time and coordination, and they can lead to mistakes. With automation, however, you get alerts whenever issues arise or new workloads are discovered, and policies can automatically move data sets to archive when they meet specific criteria. By automating policy, you can be sure that your systems will stay in compliance.
Second, focus on an approach that looks to simplify data management. The amount and speed at which data comes at us today can be overwhelming. Your data management systems must work to simplify the processes and the user interface must be intuitive. While it’s tempting to use dozens of tools to get the job done, that approach can be expensive and complicated, and takes more workforce or a diversely trained workforce. Don’t compromise, however, on the ability to protect, manage and monitor workloads across environments with a single, consolidated view.
Third, take advantage of expert guidance. You don’t have to – and shouldn’t – go at it alone. Talk to your counterparts at other agencies, interview multiple vendors, and get expert guidance from organizations like Gartner and Forrester. Taking the time to ask questions can be the difference between choosing a good solution and an excellent solution.
This article is an excerpt from GovLoop Academy’s recent course, “Holistic Approach to Data Management Is Your Only Real Option,” created in partnership with Commvault. Access the full course here.