Gartner estimates that data volume will grow 800 percent during the next five years. 80 percent will be stored as unstructured data, which includes files such as emails and images that don’t reside in a traditional database format. The explosive growth of unstructured data, which doubles in volume every three months, is creating a major headache for IT managers.

Distributed IT environments with multiple remote sites place heavy demands on IT resources, especially storage. If you follow the traditional approach and constantly add storage capacity, you’ll blow up your budget. At the same time, managing, securing and storing a never-ending flow of unstructured data across a number of branches often leads to fragmented resources and poor utilization. From a user perspective, it can be difficult to simply remember a file name and where that file was stored.

Another major challenge is regulatory compliance, with requirements that are constantly changing and tend to become stricter with every high-profile security breach. Thousands of new pieces of legislation are pending, especially in heavily regulated industries. Organizations are scrambling to get a handle on new mandates in order to avoid a spike in data management costs, heavy fines and a tarnished reputation. While structured data is relatively well-defined and easier to navigate with traditional applications, unstructured data introduces a massive layer of complexity that is difficult to manage.

Organizations can be better equipped to manage the rapid growth of unstructured data by implementing a data governance program. Data governance refers to an organization’s data management strategy and processes. Components of data governance include:

  • Identifying owners of data assets and parties responsible for ensuring that data is accurate, accessible, consistent, complete and updated.
  • Establishing processes for data storage, archival, backup and security.
  • Developing procedures that govern how data should be used by authorized parties.
  • Creating procedures to ensure compliance with industry regulations.

A data loss prevention (DLP) strategy is a critical component of data governance. DLP involves the policies and software that are used to prevent sensitive company data from leaving the network and to detect a potential breach. Managers create business rules that are used to tag sensitive data, such as intellectual property, and deny the intentional or accidental disclosure of that information. There has been a growing demand for data governance and DLP due to insider threats and strict privacy laws that have rigid requirements for data protection and access.

DLP should be integrated with both standard and advanced security measures as part of a robust security infrastructure, which is managed and audited according to a defined security policy. Standard security measures include firewalls, intrusion prevention systems, antivirus software and threat management systems, which locate, prioritize and track security patches and fixes. Advanced security measures provide greater protection by monitoring network traffic, conducting additional user verification procedures and recognizing abnormal system behavior. There are also solutions designed specifically for DLP that will detect and block efforts to expose certain data, which can be valuable if an authorized party attempts to access data that falls outside of their user profile.

Let ACS show you how a carefully planned data governance program and DLP can guide the management of unstructured data, minimize risk and keep your sensitive data safe.