![]() If you need user-specific algorithms, it is also possible to extend the existing algorithms with the new Analytics Lambda functions, which can be implemented with the help of a wizard. You can easily drag and drop the various algorithms from the toolbox into the configurator, link them with your data and other algorithms, and parameterize them according to your ideas. For this purpose, the TwinCAT 3 Analytics Workbench with the integrated configurator offers the best possibilities. Once the appropriate data has been selected, suitable algorithms and links must also be found. This provides a quick overview of individual data collections and also allows data from different data collections to be cut and linked to form a new data stream. The Data Scout, which is integrated in the TwinCAT 3 Analytics Workbench and in the TwinCAT 3 Analytics Service Tool, can help you with this. Therefore, relevant data streams and, if necessary, time periods and events must first be identified. ![]() This is because it is not always clear from the outset which data streams need to be processed using which algorithms in order to arrive at a meaningful analysis chain that delivers the desired results and recommendations for action. In many cases, the path to a successful analysis leads first through data pre-processing and exploratory pre-analysis of the data. ![]() How is a problem-specific analysis designed? How is the data processed and made available for the analyses? Step 3: Data preparation and exploratory (pre-)analysis ![]()
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