Why Investing in Unstructured Data in Your Business

Many organizations still focus their efforts solely on Structured Data, stored in databases, spreadsheets, and enterprise systems. While this data is essential for traditional analytics, it represents only a small portion of the information truly available within operations. The emerging trend, as highlighted by Gartner, is the investment in Unstructured Data.

A significant portion of valuable business knowledge is present in content that doesn’t follow a structured format, such as documents, emails, images, videos, and messages. According to IDC, 90% of corporate data is unstructured, which highlights the enormous yet underutilized opportunity. When this information is analyzed using technologies like AI and automation, it can generate strategic insights that were previously scattered across processes.

What Is Unstructured Data?

Unstructured Data refers to information that does not follow a fixed organization or storage model. Unlike Structured Data, which is organized into tables or relational databases, this type of information can come in various formats, such as text, multimedia files, documents, or digital records.

This type of data is constantly generated through daily business interactions, including internal communications, operational records, and customer support logs. Since they are not organized into standardized structures, they require specific technologies to be interpreted and analyzed. Nevertheless, they represent an extremely rich source of information to understand processes, behaviors, and opportunities for improvement.

Unstructured Data vs. Structured Data

The key difference between Structured and Unstructured Data lies in how they are organized and stored. Structured Data follows a standardized format and is easily organized into rows and columns within databases or spreadsheets, allowing for relatively simple queries and analysis.

In contrast, Unstructured Data does not have such a fixed pattern. It may exist in documents, multimedia files, communication logs, or various digital content, making its analysis more complex. However, this type of data often carries much more context and information, being essential for more advanced analytics and the generation of strategic insights.

Intelligent Document Processing

To transform Unstructured Data into useful information, many companies are adopting Intelligent Document Processing (IDP) solutions. This approach combines artificial intelligence, automation, and natural language processing to interpret content that previously required manual analysis and interpretation.

With these technologies, documents such as contracts, invoices, forms, or reports can be processed automatically, allowing systems to identify relevant information and integrate it into operational workflows. This reduces repetitive tasks, increases data reliability, and accelerates processes that previously depended on human analysis.

Extraction, Validation, and Semantic Understanding

The first step is data extraction, where the technology automatically identifies relevant information within documents or digital files. Next comes validation, which compares the extracted data with business rules or corporate databases to ensure consistency and quality.

Finally, semantic understanding enables systems to comprehend the context of information within documents. This capability enables systems to comprehend the meaning of content and support informed decision-making within processes, significantly enhancing the value of Unstructured Data.

Challenges with Unstructured Data

Despite its strategic potential, working with Unstructured Data presents several important challenges for organizations. The first is volume, as the amount of data generated daily grows rapidly across documents, digital records, media, and communications.

Another challenge is variety, as these data can exist in different formats and origins, making standardization and analysis more difficult. Additionally, there’s the issue of data quality, as incomplete, duplicated, or inconsistent data can compromise analytics and decision-making.

Finally, there’s the challenge of analysis, which requires advanced technologies capable of interpreting textual, visual, or contextual content. Without the support of AI and automation tools, much of this information remains underutilized within organizations.

How Smarthis Can Help You

If your company is not yet exploring the potential of Unstructured Data, you may be missing out on valuable information that could improve processes, reduce operational effort, and support strategic decisions. With the right technologies, it’s possible to transform documents, records, and scattered content into usable data within operations.

Smarthis helps organizations identify opportunities, structure data, and implement automation and AI solutions capable of activating this information within business processes.

Want to learn how to apply this in practice in your company? Speak with an expert today.