Unstructured Data Management: Why it’s Critical and How to Solve the Challenge

Every organization has unstructured data, which is often referred to as the “junk drawer” of data due to its different file formats, varying sizes, and lack of clear organization. For IT professionals, managing unstructured data is a significant challenge as it can be difficult to analyze, store, and gain a complete picture of it. In this article, we’ll explore why it’s crucial to have an accurate, full picture of your unstructured data and the methods to manage it efficiently.

The Difficulty of Sharing Information about Unstructured Data

Unstructured data is notoriously tricky to manage because of its size, complexity, and varied formats. Most organizations resort to free tools to scan their file systems and obtain capacity and file count details for planning. However, these tools offer limited insights into the data. Therefore, they can’t provide any meaningful analysis or intelligence. Furthermore, sharing information about unstructured data is challenging since it’s fragmented across different departments and business units. Manually collecting and consolidating data from various sources is nearly impossible. Hence, IT professionals struggle to have a complete view of their organization’s unstructured data.

Despite these challenges, having an accurate and complete view of your unstructured data is critical. Companies rely on data to make decisions, and unstructured data can be a goldmine of information. However, if IT professionals are unaware of what data is present, where it’s located, and how it’s being used, it can lead to significant risks. For instance, sensitive data could be exposed to unauthorized users, and data preservation and retrieval could become expensive and time-consuming. Therefore, to conduct business safely, efficiently, cost-effectively, and successfully, having a complete picture of unstructured data is crucial.

Blind Decisions and End-User Management of Unstructured Data

No other area of IT makes decisions about their platform so blindly and leaves their end-users to manage such a large portion of it. Often, business units own and store their unstructured data in silos, with no oversight or accountability. This lack of centralized management can lead to user frustration and contribute to the growth of “data sprawl.” IT professionals must have better control over unstructured data to optimize resources, improve security and compliance, and mitigate risks.

Historically, unstructured data management tools have offered limited information about the specifics of the data. As a result, IT professionals may have had some insights into the data’s size and format, but they couldn’t determine its location, ownership, age, or the cost to the organization. This lack of detail made it challenging to apply policies or determine the most efficient storage options.

The Lack of Responsibility for Unstructured Data

As mentioned earlier, unstructured data is often fragmented across different business units with no clear ownership or responsibility. Business units often hold onto their data even after the original data owners leave the organization, leading to data with no clear owner or accountability. Furthermore, the lack of centralized management means that there’s no one looking after the data’s integrity, quality, or accuracy. In short, no one knows what’s in a company’s data “junk drawer,” and there are no clear processes for managing it.

Solutions for Managing Unstructured Data

Fortunately, solutions for managing unstructured data are available. These solutions offer insights into top users and groups that consume capacity, orphaned data whose owner has departed, the cost of datasets, associated emissions, and the age of data. These insights help IT professionals take real actions and make informed decisions. Tagging data is another useful ability that helps teams organize and assign ownership to datasets. By tagging data, IT professionals can better understand its purpose, location, and owner, thus better positioning them to optimize the storage of data and make more informed decisions about its use.

The importance of gaining insights on top users and groups, orphaned data, cost of datasets and associated emissions, and age of data

By understanding the top users and groups consuming capacity within the organization, IT professionals can optimize their storage allocation to reduce their data’s carbon footprint, minimize storage costs, and support sustainable environmental practices. Orphaned data is another area of concern since it is data that has no clear owner, yet organizations still have to pay for its storage. By identifying this data explicitly, IT professionals can take action to assign ownership, archive, or delete it. Understanding the dataset’s age, usage, and format can also help with more informed decisions, such as archiving, backing up, or even deleting data to provide more space.

The Benefits of Managing Unstructured Data for the Entire Organization

Effective unstructured data management can bring significant improvements to an organization. Not only does it improve storage efficiency, but it can also support better-informed decision-making, enhance data quality and accuracy, ensure compliance with regulations such as GDPR and CCPA, and mitigate risks associated with data loss or corruption.


Managing unstructured data can be challenging, but effective management has benefits beyond storage optimization. By understanding the specifics of unstructured data, IT professionals can make better-informed decisions, reduce costs, and improve efficiency. Ultimately, managing unstructured data is an essential step towards achieving data-driven success, which requires having accurate data insights at your fingertips.

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