Need to know: Text analyser or insight engine?
Advanced cognitive technologies are now able to add context to content, converting information into knowledge. Serious Digital transformation takes advantage of their firm’s unstructured data.
A large portion of internal or external content that organisations rely on to do business—records, news feeds, web content, emails, presentations, customer feedback, market reports, compliance documentation — is classified as unstructured data.
The very nature and quantity of this information make it both difficult to manage and extremely valuable to make good decisions. Convert unstructured information into the right kind of structured data has been a challenge for most enterprises.
The more advanced cognitive technologies are now able to add context to content, turning information into knowledge, and supporting understand of complex documents. To be serious about digital transformation, records, and information managers’ organizations need to take steps to take advantage of their firm’s unstructured data.
Cognitive technologies make many new ways of working possible, including:
- More effective than Google searching for real-time insight and knowledge discovery.
- Mitigate risks such as operations, reputation, competitor activity. through information analysis and monitoring.
- Automatic routing and data extraction from emails
- Know what competitors are doing and intercept market trends
- Back-office automation where processes have traditionally required a lot of reading
- Improved customer interactions by extracting data from forms, chats, and voice recordings.
When looking for text analysers:
- Know semantic and linguistic challenges for words relevant to your knowledge domain.
- Eliminate any solution that requires large training sets – you should be able to get a good result from a proof of concept of around 100 documents.
- Select only those with explainable results and where the context of documents is in an understandable form.
- Expect that the software capability is flexible and accurate enough to meet many of your use cases without a data scientist on the payroll.