1. Data Extraction Solution for Dark Data
Most of the data generated and stored in the course of a company’s operations is what is known as “dark data,” data that is never actually used. It is important to the future of both society and companies that this routinely collected data be collated and analyzed to turn it into meaningful information for use in resolving challenges and helping to create new value.
This solution uses a technique for the structural analysis of information representation that determines the structure of documents from a variety of features, including tables, figures, and visual information, and a dark data analysis engine based on weak supervision, a learning technique that can generate artificial intelligence (AI) models from small amounts of training data. Together, these enable the solution to efficiently extract structured data from unstructured formats that have proven difficult to interpret in the past.
By enabling the use of data from non-standardized forms, that is forms such as invoices and medical billing documents that vary in format and terminology depending on who issued them, the solution can speed up management decision making and facilitate business reform by helping companies overcome the challenges of improving productivity and cutting costs.
Along with further functional enhancements, Hitachi is also working on measures to help customers resolve challenges and create value in a wide range of different ways by combining this solution with others such as analytic AI.