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Analysis dashboards let you review and visualize data from any step of a pipeline. You can quickly move from raw data to visualization by describing the insights you need to the Agent, which automatically generates both the underlying pipeline and the resulting analysis. You can iteratively refine the Agent’s output until the results meet your requirements. For production workflows, you can integrate oversight from your data team into this process. Data engineers can optimize Agent-generated pipelines to ensure data integrity and performance. Multiple business users can then interact with the final dashboards to explore data independently within the guardrails established by the engineering team.
Before Prophecy 4.2.5, analysis dashboards were known as Prophecy Apps. We have renamed this feature to more strongly couple analysis with pipelines. Functionality remains largely the same; however, now you can interact with the analysis using Prophecy Agents.

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Use cases

You can build an analysis dashboard to serve a variety of use cases. We’ll highlight two mental models for building analyses here; these can help you decide how to create the analysis that best serves your requirements. You can think about creating analyses in two ways:
  • Fixed dashboards: Always run the pipeline on the same sources. The data may change, but the pipeline is always the same.
  • Interactive dashboards: Show results based on user input. Depending on how you build the dashboard, users can do things like upload their own data or change the parameters of the pipeline.

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Fixed dashboards

Fixed dashboards display results from pipeline runs without requiring user input. They’re perfect when you want to:
  • Preview pipeline outputs before publishing to BI tools.
  • Schedule regular reports with different parameter configurations.
  • Share a specific analysis or report with stakeholders.
When you create a fixed dashboard, you include data and content components. You don’t include any interactive components.

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Interactive dashboards

Interactive dashboards let users customize inputs and run pipelines on demand. They’re ideal when you want to:
  • Enable team members to answer their own questions without writing code.
  • Provide guardrails that guide users toward correct, tested execution paths.
To make a dashboard interactive, you’ll need to include interactive components as you build it. Interactive components let users:
  • Upload custom data to replace pipeline input sources.
  • Set pipeline parameters (dates, thresholds, regions) through simple form fields.
  • Save personal configurations while maintaining a shared, standardized pipeline.

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What’s next?