3 min.

Unstructured Data

Data plays a fundamental role in today's business world, which is why a comprehensive understanding of data is more important than ever in the age of digital transformation. A basic distinction can be made between three main types of data: structured, semi-structured (semistructured) and unstructured data. This article will focus on the latter type of data: As a pioneer in AI-based data processing of unstructured formats, we have summarised everything you need to know about this topic.
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What is unstructured data and why is it important?

Unstructured data is available in its raw form, so to speak: By definition, it has no organisation or structure. A concrete example of unstructured data is a document without predefined formatting. In the healthcare sector, this could be parts of a patient file, for example notes that doctors have jotted down (perhaps even handwritten) during examinations.

The processing of unstructured data is therefore complex and time-consuming. It is precisely in the (apparent) chaos of structured data that an opportunity lies: Despite this challenge, unstructured data can be or be assigned metadata that definitely has a certain structure. This metadata provides context and information that can facilitate the analysis and interpretation of unstructured data. In a document from the insurance industry, for example, metadata could be the policy number, the person responsible, the contract term or similar. In the healthcare sector, it could be the date of birth or blood group. The metadata therefore provides an overview of the document and makes it easier to analyse.

The importance of unstructured data

The majority of information that companies come into contact with on a daily basis is unstructured data: Emails, reports, text documents, images and more. Unlike structured data, it has no predefined organisation or formatting. Although unstructured data may seem chaotic and perhaps overwhelming at first glance, its value lies in its versatility and wealth of information. Since unstructured data has no predefined schema, it can be used in a variety of contexts. This versatility makes it extremely valuable in today’s data-driven world. In a world where information is the key to competitive advantage, organisations that understand and leverage the importance of unstructured data can gain a decisive edge. The ability to extract valuable insights from seemingly chaotic data opens doors to innovative strategies, informed decisions and ultimately improved business performance. Unstructured data is therefore indispensable for data-driven business strategies in particular.

One platform,
endless possibilities.

ExB is an Intelligent Document Processing platform that transforms unstructured data from any type of document into structured results. Our AI-based software can not only extract all relevant information from your documents, but also understand them. This allows you to automate your processes and save both time & money, while improving your customer experience and employee satisfaction. Win-win. 


Challenges in the processing of unstructured data

Unlike structured data, unstructured data lacks an organisational structure. This is why its processing requires complex algorithms and techniques. As a result, traditional databases and analysis methods are often inadequate.

Relational databases

Relational databases are an important pillar of modern data processing. They are primarily designed for the efficient storage and management of structured data, but can also be associated with unstructured data. Modern relational databases can manage unstructured data in databases using technologies such as CLOBs (Character Large Objects) and BLOBs (Binary Large Objects). However, relational databases are not optimal for processing unstructured data; specialised data processing platforms are more suitable.

Analyse unstructured data

As the processing of structured data is by no means a trivial task, AI-supported tools or platforms are typically used. Processing structured data not only requires specific techniques and software, but usually even a combination of these technologies.

Document processing with ExB

Unstructured data is no problem for ExB: our advanced and unique platform utilises a combination of technologies, including machine learning and artificial intelligence, OCR, NLP and computer vision. ExB easily converts multi-layered and unstructured data into actionable or structured data to drive data-driven business strategies and automate repetitive workflows, for example.

Overall, unstructured data is a valuable but often underutilised resource. The ability to analyse, understand and use this data can make the difference between successful business strategies and missed opportunities. Platforms such as ExB’s innovative IDP platform offer a solution to maximise the value of unstructured data, paving the way for a data-driven future.


Written by:

Dr. Ramin Assadollahi

CEO & Gründer ExB

Dr. Ramin Assadollahi is a computational linguist, inventor and clinical psychologist and is considered one of the AI thought leaders in Germany.
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