Tapping into the Unstructured Data Goldmine for Enterprise in 2025

Companies are overwhelmed by data. A majority of organizations (64%) manage at least one petabyte (PB) of data, while 41% surpassing that with at least 500 PBs of data, according to the AI & Information Management Report.

As companies amass vast amounts of data, the process of managing and leveraging this data to drive better business decisions becomes more complex, especially with the growth of unstructured data–which is any file or information that doesn’t fit into traditional database structures.

An “elephant in the room” problem facing every organization, unstructured data is comprised of digital video files, documents, text files, emails, images, and even social media content. It also represents untapped value because unstructured data–a primary component of dark data–is not being classified, so it cannot be readily used. In fact, according to Deloitte, only 18% of organizations are able to leverage this data.

The Hidden Danger and Value of Unstructured Data

Because unstructured data is in various formats (text, images, audio, video), it’s difficult to standardize. Inconsistent unstructured data formats across datasets also increase the difficulty in maintaining high-quality data. This makes unstructured data harder to monitor and secure compared to structured data. Sensitive information embedded in unstructured formats like documents, emails, or social media content may not be as easily identifiable. This can lead to fines for non-compliance with HIPAA, GDPR or CCPA if unstructured data sets contain personal or sensitive customer or employee data.

(Yurchanka-Siarhei/Shutterstock)

With so much structured data on hand, companies may believe unstructured data doesn’t add value, which couldn’t be farther from the truth. In fact, unstructured data can provide deeper insights and put companies ahead of the competition. However, before that happens, organizations must get a handle on all of the data they have on hand. While the majority of unstructured data is digital, some businesses have a large number of paper records that haven’t yet been digitized. By using a combination of software and document scanners, hard copies can be scanned and integrated with unstructured data.

This may seem like too much of an investment from a time and resource perspective, and a heavy lift for humans alone; however, AI can fundamentally change how companies leverage unstructured data, enabling organizations to extract valuable insights and drive decision-making through human/machine collaboration.

Automate Data Collection, Then Organize It

For a more organized approach to structuring unstructured data, start by using an AI tool that will automate the process of data collection. Microsoft Azure Cognitive Services, Tableau and DataRobot are a few options for automating the collection and ingestion of unstructured data from various sources like emails, websites, or IoT devices.

Multimodal AI models can analyze images and videos to recognize and classify objects, people, or scenes, tagging and sorting images in a photo/video library based on what’s in the content. AI is also useful in cleaning up “noisy” or irrelevant data in unstructured sources, such as filtering out spam emails, irrelevant text, or removing artifacts from low-quality images.

Once the unstructured data is collected, it can be organized into categories, such as text, audio and images, to facilitate easier management and retrieval. During this phase, metadata tags – for keywords, author, and creation date, for example – can improve searchability and categorization. Data labeling can further simplify classification by using tags that clearly define topics or sentiment, grouping them for easier analysis.

AI is also effective at combining unstructured data with structured data to enrich insights. One example of this is adding contextual information from social media content or customer feedback on purchase data or transaction history to create a richer dataset that drives more insightful analysis.

The Unified Data Gold Strike

There’s no doubt that effectively managing unstructured data is critical to a successful and holistic data management program, but managing it can be complex, overwhelming, resource-intensive and difficult to analyze because it doesn’t fit neatly into traditional databases. Unlike structured data, which can easily be turned into business intelligence, unstructured data often requires significant processing before it can provide actionable insights.

Luckily, there are plenty of business intelligence tools, such as Tableau and Power BI, that can effectively visualize insights drawn from unstructured data for better decision-making. When unstructured data is analyzed, it can enhance predictive models by providing a more holistic view. For instance, combining structured data (like sales figures) with unstructured data (such as customer conversations or product descriptions) can reveal deeper patterns and correlations, improving forecasts and helping organizations make more informed strategic decisions.

While unstructured data can offer valuable insights and help organizations make better decisions, its complexity, resource demands, security concerns, and integration challenges require careful oversight and management. Organizations must adopt the right technologies and processes to mitigate the downsides of unstructured data and maximize its business value.

About the author: Scott Francis, Technology Evangelist at PFU America, Inc., brings more than 30 years of document imaging expertise to his position where he’s responsible for evangelizing Ricoh’s industry leading scanner technology. With over thirty years of experience in the enterprise content management industry, he frequently provides thought leadership on document scanning use cases and best practices in addition to the overall benefits of digital transformation solutions.