Simplify Collection, Reporting and Analysis with Wonderware Intelligence
Industrial operations typically leverage multiple software systems to manage the day by day operations in an effective and secure manner. These systems can generate large amounts of data (industrial Big Data) across multiple systems – but users lack the ability to analyze this data in context. It becomes almost impossible to understand which actions and events have the greatest impact on production performance, quality and sustainability, or overall business performance.
Wonderware Intelligence solves this problem by offering a standard software approach to extract, transform and store a history of operational performance and sustainability metrics from one or across multiple data sources quickly and easily. With “out-of-the-box content” and pre-configured information models, Intelligence pulls together disparate data into a common contextualized structure for easy reporting and analysis. Once these data models are set and deployed, the software extracts transforms and loads data from all data sources into a data store structured according to the designed information model – and the system continues to refresh this store as often as needed. As a result, Wonderware Intelligence provides an always up-to-date data store, optimized for retrieval. This information can then be used to monitor key performance indicators or can be leveraged for responsive root cause analyses for insights into operational performance, sustainability and relationships between operational and business performance.
Once stored, users can simply report off of this data store using SQL Server Reporting Services or access and analyze this pre-contextualized data through a variety of tools such as:
– Microsoft BI
– Business Objects
To learn more about Wonderware Intelligence and to see a live demo of the solution, join Wonderware North and Schneider Electric for this free webinar:
Topic: Simplify Collection, Reporting and Analysis with Wonderware Intelligence
Date: Wednesday, January 25, 2017
Time: 2:00 pm EST
Click here to register for this free webinar.
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