Unstructured Data Management: Turning a Complex Task into Something Easy with AI

Valuable data drives organizations and industries forward. While structured data is available for most organizations, about 80 percent of the information an enterprise accumulates is unstructured. The information comes from various images, stored information, emails, voice recordings, and social media posts, and the volume presents a challenge to an organization.


Understanding unstructured data

Managing unstructured data is a complex task. However, tech companies are developing solutions to simplify data management.

As businesses and industries rapidly shift to digital, more unstructured data becomes available from business systems, client touchpoints, and various devices. As a result, it presents challenges for developing a strategy to manage them while ensuring that the information remains regulation-compliant, secure, and confidential.


Moreover, since unstructured information does not have a unified format, it needs a data management platform to keep them in one place that is accessible and secure because unstructured data also contains business and personal information critical to business operations.


Easier unstructured data management

Data science is now a powerful discipline ready to tackle big data. But instead of handling a very complex task, it could make the job easier with artificial intelligence. AI continues to evolve and play an increasingly vital role in managing volumes of data, specifically unstructured information. About two-thirds of existing companies agree that machine learning and artificial intelligence are central to their data analytics and platform initiatives.


AI helps to eliminate the challenges of data science by automating the process of understanding and extracting value from varied and large sets of data. AI helps organizations manage and get insights from data that are difficult to access, improving productivity and decision-making.

Manual data processing is no longer viable with the constant and steady demand for business intelligence. Thus, many companies are using artificial intelligence and machine learning to add consistency, accuracy, and speed to their data processing.

To manage unstructured data, AI uses several tools


  • Natural language processing (NLP). The text information you get online is unstructured. It includes social media posts, emails, reviews, and other documents, which are excellent sources of business insights. NLP makes sense of the information by understanding the meaning of the words and their relationships.
  • Sentiment analysis. Also called opinion mining, this one used to be a branch of NLP but is now a standalone solution. It uses NLP machine learning and text analytics to identify and draw out subjective information from comments and reviews. It is now a tool for online reputation management and digital marketing.
  • OCR. Optical character recognitionis often employed in sectors requiring much documentation, such as healthcare and finance. OCR extracts handwritten/machine-written text from image files and translates them into machine-readable characters. The system then integrates the collected data into the business workflow for report generation.
  • Computer visionis high-level AI technology that enables computers to see and understand the world like humans. It uses machine learning algorithms to identify, isolate, and classify videos and images. It is integral in the data analytics environment. For example, it can automatically assess a product’s quality.

You can see how artificial intelligence helps by turning unstructured into structured data. With AI easily performing the process, you can increase your business efficiency and make better decisions.