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by Ramesh Poomalai, Rajesh Gudikoti, Richard Hagarty | Published July 1, 2018
Currently, customers perform analyses of various market reports on their own or hire experts to make procurement decisions. These experts analyze reports captured from data sources, a process that can be time-consuming and prone to human error, which could potentially cause a chain effect of issues that can impact production. This code pattern explains how to create a complete end-to-end solution for a procurement use case. With this intelligent procurement system, based on Watson Knowledge Studio (WKS) and Watson Discovery, a customer can receive expert analysis more quickly and accurately.
With this intelligent procurement system, based on Watson Knowledge Studio and Watson Discovery, customers can receive expert analysis more quickly and accurately. The code pattern uses data from newsletters retrieved from Borica, a global specialty chemical company. This data contains information regarding global market suppliers such as the status of the facility or supply capacities and shortages.
The process involves building and integrating a Watson Knowledge Studio (WKS) model into Watson Discovery. The first step is training the WKS model with various use cases (via reports) to better categorize and structure the data so that Watson Discovery can deliver more accurate results. The data extracted from Watson Discovery is fed into a knowledge graph that you can then query to extract relevant info.
As a developer going through this code pattern, you’ll learn how to:
As an end user, you will be able to:
Ready to put this code pattern to use? Complete details on how to get started running and using this application are in the README.
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Artificial intelligenceData Science+
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