The storage and organization of documents have been a problem even before the advent of computers.
Companies before used physical filing. Although it was an ineffective method, it was the best method during those times.
The emergence of computers was supposed to solve that problem and make it easier to store, organize, and pick up documents when needed.
Sadly though, the digital age has not seemed to sort out this drawback, at least until Microsoft’s SharePoint Syntex.
The formal introduction of SharePoint Syntex from Project Cortex provides a solution to help you automate the extraction of metadata from your files, making it easy for you to build processes that can automatically capture and process data.
To better understand how to create a data organization system to cater to the huge amount of data in your company, it’s important to understand SharePoint Syntex.
In this article, you will learn about what SharePoint Syntex is, why you should do it, and how SharePoint Syntex works.
Table of Contents:
SharePoint Syntex is a Microsoft 365 service from Project Cortex that helps organizations:
- Automate data and content processing
- Utilize advanced AI and machine learning to augment human experiences
- Modify content into knowledge
By design, it’s a tool to help companies and businesses better manage a large amount of content they have to deal with to boost their efficiency.
SharePoint Syntex gathers information from content, creates and applies metadata to a SharePoint library, and then utilizes models. The content is then transformed into knowledge.
Depending on the models set up by you — the user — content is labeled and arranged by SharePoint Syntex before extracting specific data.
Sensitive information can easily be protected as SharePoint Syntex can apply retention and sensitivity labels to sensitive information.
SharePoint Syntex has two major methods of data classification and extraction:
1. Form processing
This method is great for extracting metadata from files that are always structured, such as surveys, invoices, purchase order documents, addresses, geolocation, and stock information.
In instances where the user has to extract information from large amounts of structured content, images, and pdf files, form processing is the best way to extract the needed information.
The form processing method is built on the AI Builder component of the Microsoft Power Platform and therefore allows the user to set up the exact location of the field on any given form.
After the model has been set up, the AI Builder automatically reads and extracts the metadata from the already defined field locations from future files that are uploaded.
The information that the AI Builder extracts is stored within SharePoint columns allowing the user to be able to search to recover content that has been captured by metadata and also sort and group by the values extracted automatically.
For example, a user can create a form processing model tasked with identifying all invoices uploaded to the document library. The user can then extract and display the specific data they want, such as total cost, date, or PO number.
2. Document understanding
This method utilizes artificial intelligence (AI) models to automate the classification of files and extract information.
Document understanding models are created and managed in the content center. When applied to a SharePoint document library, the model is correlated with a content type and columns to store the extracted information.
The content type created is subsequently stored in the SharePoint content type gallery.
The document understanding method is best for unstructured documents such as contracts, letters, emails, webpages, media files and revolves around two major concepts — classifiers and extractors.
These unstructured documents must have text that can be identified based on phrases or patterns, used to classify the type of file, and extract the file you want to extract.
Classifiers are trained to identify and classify documents uploaded to the document library while extractors retrieve information from these documents.
Here are some examples:
- A user can train a classifier to identify all company emails uploaded to the library based on the type defined by the user when creating the classifier.
- A user can create a column display to extract specific information from all company emails identified in the document library.
Which method is the best to use?
Both methods are a great option to extract information from a large content depending on the type of data you want to extract.
If you want to extract information from large and consistently structured data, forms processing is the best method to use.
However, if you want to extract information from large but hugely unstructured data, then document understanding is the best method to use.
Imagine a large number of content companies and businesses have to process daily.
Typically, the process of tagging, storing, organizing, and extracting information can be tedious and wearisome.
For those still wondering why they have to use this tool, below are a few reasons:
- SharePoint Syntex is a great way to save a whole chunk of significant time that would otherwise have been used trying to sort through a large amount of content available.
- The SharePoint Syntex tool helps to make it an easy and stressless process of trying to organize and extract specific information when you need it.
Finally, having an automated process that can be trained is a welcome development, especially in this digital age.
The launch of SharePoint Syntex is a thrilling innovation:
With further advancements expected, such as an automated AI processing that understands the meaning of content well enough to automatically classify all files once it grows out of its infancy stage, it’s only compelling to think of what comes next.
Exciting times lie ahead as Project Cortex evolves the features and capabilities of the Microsoft 365 tool to become the center of companies and businesses’ content processing.
So what do you think of Microsoft SharePoint Syntex? Are you planning on using it soon?
If you have any questions, feel free to drop them down in the comment section. For inquiries, send me a message on my contact page and I’ll get back to you as soon as possible.