Why is data remediation misunderstood

Data Remediation is often misunderstood as a simple process of removing business data which you no longer need. But in reality it means a lot more than just what we think. In enterprise environments, before embarking on a large scale data migration from a legacy system into a new system, it is important to establish a new game plan. Part of a game plan is to profile the data that will be migrated and get rid of the one which is not useful to the organization anymore. Here data removal takes places in three cases.

The more common use cases are securely removing old and unused legacy data systems, or eliminating personally identifiable information within company archives.

Another scenario that may not be as obvious, but is certainly a frequent request, is to manage data when employees leave companies within industries with a lot of intellectual property, such as biotech. Upon the departure of any given employee, there is often a focused remediation process whereby the outgoing employee’s work product is securely deleted and removed from his machines. For these matters, there is often an initial exit interview with counsel present to help identify the documents to remove from his systems.

Third type of remediation scenario is when two companies in a partnership are separating. As a part of remediation process, CIOs identify intellectual property related documents that Company A needs to have removed from its systems. Sometimes, company A has to also provide a copy of those identified documents related to intellectual property to company B. Here again the decision makers should work with counsel to identify documents for remediation and ensure all necessary steps are taken to securely delete or transfer the documents of interest.

  • Coming to organizations which need to understand the value of data they hold against a number of drivers
  • For public bodies like government agencies, they should first understand whether the information of public or historical interest?
  • For financial services/utilities/pharmaceutical, they should find our whether there are legal obligations that require the data to be retained?
  • On a parallel note, all organizations need to consider data protection and privacy regulations as well.

Ultimately the solution is not simply deleting or destroying data. In fact, it’s the overall management of data and while this certainly might include cleaning up redundant or duplicate files, the process is about truly understanding the data you hold.

Data remediation can now be termed as a process of deletion, organization, categorization or migration. It’s actually a five step process which is as follows-

Understanding- Enterprise dealing with remediation of data should first understand what data do they hold. It is called ‘profiling’ and it helps decision makers to comprehend what actually you need to keep and what to be thrown out. This step will help in knowing where savings can be made as many organizations pay exactly the same for storing a valuable record as one that is completely futile.

Organizing- Organizing files, records and documents will eliminate chaotic mess created with disorderly stuff. In this automation age, automatic categorization of content using machine learning alongside semantic and linguistic reasoning, making it much easier for users to find the information they require, and that too on a much quicker note.

Deleting or archiving- Many enterprise heads feel that in data remediation projects not all data should go into the trash. Here archiving non-core data to a more cost-effective storage medium such as tape or cloud like Microsoft Azure can work. With this solution data is accessible at any time and the cost reduction is significant.

Migration- Every organization’s end goal will be to consolidate all the data to a new environment, whether this is SharePoint, Office365, or Azure. With automated intelligence approach, migration is carried out in an accurate, timely and audited manner. Legacy systems can be de-commissioned, simplifying your information architecture and providing it as a fit for purpose future proof data platform.

Governance- Finally, the data that has been organized and categorized now has the security, retention and access requirements of your information policy applied to it. This application of governance requirements, in turn, reduces corporate risk and increases productivity.

Data Remediation is the buzz term of the moment in enterprise environments- and as you can see, it’s so much more than simple deletion.

Want to go for it, but do not know where to start from?

Approach DNF Corporation for your data migration and data remediation needs. DNF team is available to help you migrate your data after remediation from one environment to another in the shortest amount of time. A highly qualified consulting engineer will guide your organization through the remediation and migration process with the least amount of disruption to your end users and your overall business environment. Each remediation is unique and requires a comprehensive plan. Therefore, DNF uses the best industry practices for risk mitigation and data integrity – before, during, and after the remediation process.


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