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  • Data view: The data view that the engine will be analyzing.
  • Analysis group: The nature of the analysis. This could include outlier detection, time period comparison, or changes in trend. Each analysis type is linked to algorithms that allow Yellowfin to look for related patterns in your data. 
  • Key Date field: This will become the basis of your time-series data around which changes are detected.
  • Time window: Specify the exact time period which you would like the system to analyze.
  • Schedule: You can take full advantage of the automation aspect of Signals, by setting up a flexible schedule to run them periodically.
  • Metric and dimension fields: You will need to specify the relevant metric and dimension field to analyze.
  • Filters: You may also use filters to apply conditions on the data that you want analyzed.
  • Parameters and thresholds: A set of advanced configurations is provided based on your selected analysis type. This gives you a chance to go deeper into the algorithm’s specifications, such as providing threshold values.
  • Users: You can choose the audience who will receive the Signals, so that only users who need the insights will receive them. In case of a multi-client organization structure, you can limit the Signals to be accessed by specific client orgs.

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signalinstructions
signalinstructions

Instructions

Follow the instructions below to set up an automated Signals analysis job.

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