AN01 - Analytics Usage
ℹ️ This Automic Course is part of PEM Automic and was published on March 14th 2025.
📋 Content: 2 lessons and 1 final test
🕒 Duration: Depending on your experience as a designer, around 40 minutes.
In today's data-driven world, well-founded decisions are hardly possible without a solid database. But what if your Automic database only stores minimal statistical data? This is where Automic Analytics comes into play! In this article, you will learn how to use dashboards and widgets to gain valuable insights from your statistical data.
Why is Automic Analytics important?
The Automic database only stores the most essential statistical data to ensure optimal performance. But if you want to know whether there are more jobs running today than a year ago, you need long-term data storage. Automic Analytics offers precisely this possibility by storing statistical data in a PostgreSQL database. Since this is done outside the Automic database, your system remains efficient.
What data is stored in Analytics?
Automic Analytics stores aggregated statistical data such as:
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Task duration
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Task status (successful or failed)
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Assigned agent
However, no comprehensive reports are stored in Analytics - there is purely the statistical data.
Dashboards and widgets for better visualization
The stored data is accessed via dashboards with various widgets. Each dashboard contains a data source that determines which data is displayed in the widgets. For example, you can create a dashboard for jobs only that does not display any workflows.
Conclusion: More transparency and better decisions
Automic Analytics provides you with a powerful solution for long-term storage and visualization of your Automic data. Thanks to dashboards and widgets, you can always keep an eye on important figures and evaluate your data efficiently.Learn Automic with PEM!
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FAQ about Automic Training on PEM
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