Unstructured data refers to the vast amounts of information that is not organised in a specific manner, such as text documents (contracts, articles, white papers), emails, survey results, customer feedback and social media posts. While this type of data may not immediately appear to have value, there are various methods that organisations can use to extract valuable insights and information from it.

One of the most common ways to obtain value from unstructured data is through the use of natural language processing (NLP) techniques. NLP is a field of artificial intelligence (AI) that focuses on the ability of computers to understand, interpret, and generate human language. By applying NLP algorithms to unstructured data, organizations can automatically extract key phrases, entities, and sentiments from the data, providing valuable insights and information. Infoboss uses NLP as one technique to help classify text.

Another method for obtaining value from unstructured data is through the use of data mining techniques. Data mining involves the process of automatically discovering patterns and relationships in large datasets. By applying these techniques to unstructured data, organisations can identify trends and relationships that would be difficult or impossible to find manually. Infoboss uses these techniques to find and classify data. It can also leverage these discoveries by augmenting the metadata associated with the unstructured data asset. Perhaps identifying customer reference numbers and then adding the customer orders and satisfaction scores to the metadata associated with the document text.

There are several benefits to be realised from obtaining value from unstructured data. Firstly, it can provide organisations with a more comprehensive view of their operations and customers, allowing them to make more informed decisions. For example, by analysing customer feedback and social media posts, organisations can gain insights into customer preferences and pain points, enabling them to improve their products and services.

Secondly, obtaining value from unstructured data can help organisations to improve their efficiency and productivity. By automating the process of extracting valuable information from unstructured data, organisations can save time and resources that would otherwise be spent on manual data analysis. This can enable organisations to focus on more important tasks, such as developing new products and services or improving existing ones.

Thirdly, obtaining value from unstructured data can help organisations to gain a competitive advantage. By using NLP, data mining, and other techniques to uncover insights and trends that others may not be able to see, organisations can gain a better understanding of their market and customers, allowing them to make strategic decisions that give them an edge over their competitors.

In conclusion, while unstructured data may not immediately appear to have value, there are various methods that organizations can use to extract valuable insights and information from it. By applying NLP, data mining, and other techniques to unstructured data, organisations can gain a more comprehensive view of their operations and customers, improve their efficiency and productivity, and gain a competitive advantage.