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Managing the challenges of unstructured data 

Managing the challenges of unstructured data 

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Scotty Calkins, Sr. Systems Engineer, Datadobi, discusses four key current challenges of managing unstructured data and evaluates potential solutions.

Let’s face it: today’s unstructured data environments are chaotic. Masses of redundant, obsolete or trivial (ROT) data sit collecting dust on network shelves, the sheer volume of unstructured data keeps getting larger, and heterogeneous storage structures eliminate the chance of a uniform standard across a network.

The multi-vendor world we live in makes it impossible for IT to rely on native unstructured data management features from each individual storage vendor or cloud provider.

This new age we’re in is what I like to call the ‘Wild West era’ of unstructured data management. Enterprises that manage to be successful in this new frontier of unstructured data will have a serious edge over competitors, but those who fail to adapt will be left in the dust.

Scotty Calkins, Senior Systems Engineer at Datadobi

IT leaders can’t navigate it alone. Consider the following key challenges IT leaders must address if they are going to win in the unstructured data showdown against the other ‘sheriffs’ in town:

Four key current challenges of managing unstructured data:

  1. Keeping costs under control. As terabytes turn into petabytes, burgeoning demands on IT resources continue to mount. Between juggling increased budget allocation responsibly, compounding project demands, and timely sourcing of hardware, IT leaders have little time to dedicate to the unstructured data management problem.
  2. Managing carbon footprint. Environmental, Social and Governance (ESG) policies are high on the agenda of almost every major enterprise today. From sourcing responsibly to reducing carbon footprint, end-users and investors are increasingly judging the organizations they work with on their ESG performance. IT leaders must be proactive in understanding the impact of IT operations in the context of new ESG policies and guidelines.
  3. Handling risks. Unstructured data must be handled with care. While often compared to the new ‘oil’, unstructured data is more like the new uranium. IT leaders can use it to their advantage, similar to how uranium has been converted into nuclear energy, but it also presents several risks such as susceptibility to ransomware, data exposure accidents, insider maliciousness and more.
  4. Maximizing unstructured data value. All of the unstructured data sitting on a network has the ability to weave together a story about the particular company, customers, services and products. The information can direct the trajectory of an organization’s future. The problem is IT leaders need modern purpose-built tools when it comes to extracting that valuable information.7

Finding the right unstructured management solution

IT leaders need an unstructured data management solution that will act as a ‘trusted steed’ to enable them to visualize, organize and optimize their entire data landscape via one single pane of glass. Doing so puts them in the driver’s seat to control their unstructured data.

Here’s what to evaluate in potential solutions:

  1. Does the solution organize and categorize unstructured data? This allows IT leaders to understand what data they have, where it is and who owns it.
  2. Can users create automatic unstructured data management jobs? Once enterprise IT teams understand how much unstructured data they have, where it resides, the types of data they have, and how active it is, the solution should be able to enable teams to complete necessary data management projects automatically.
  3. No matter where your unstructured data lives, can the solution scan and manage it? Regardless whether an organization’s data lives in one data center, across multiple on-premises systems and the cloud, or is scattered across the globe, the solution should be able to scan and manage it.
  4. Does the solution tag the data? Can you apply user-defined tags. Identifying characteristics such as data owernship, location, sovereignty requirements, relationship to projects and so on?
  5. What does the presentation of the information look like? UI is one of the most important factors to evaluate. It should be easily accessible in a single dashboard.
  6. Does the solution present cost information? A valuable function of a data management solution should allow you to examine the cost of storing individual datasets both interms of financial cost and also in terms of CO2 emissions associated with the data. Perhaps there are more efficient locations for those datasets depending on how active they are.
  7. Does it support action tagging? Action tags allow administrators to take action on unstructured datasets of interest. For example, based on cost the decision might be made to relocate data so applying a migration action tag to the desired dataset instructs the software to execute that activity.

In summary, the solution should provide more pervasive visibility to enable smarter data decision-making and budgeting to manage cost, carbon footprint and risk while maximizing unstructured data value.

Managing unstructured data today can easily seem like it’s like being in the Wild West, but it doesn’t have to be. When equipped with the right unstructured data management solution, IT leaders can successfully navigate the challenges ahead and ride off into the sunset.

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