Updated: Nov 1, 2020
SharePoint Online and increasingly Microsoft Teams are used for teamwork and collaboration. In my experience, a significant portion of the business information created/received as part of a business activity lives in un / semi-structured documents and other file formats. In many of these situations, we can significantly improve decision making by extracting important information and applying a structure for automation and further processing.
For example, in the below video blog I have picked up an example for a leading oil and gas company, the lubricants team performs daily tests on lubricant samples and the results from multiple vendors are returned in different files formats. In most cases, the team is mainly interested in the Sample code, and the result summary to then match the code and automate the updates to their structured data system where the rest results are extracted and used for further engineering activities and decisions.
In the above use case, automated entity extraction can significantly improve the process and the timeliness with which results are processed to support further business process activities.
I am using SharePoint Syntex to create a 'Document understanding' model to extract key entities and let the SharePoint Syntex model perform the initial processing and populate the SharePoint metadata.
The key steps involved in this process are as follows: