📈 Build your own BI dashboard based on Studio exported data 🏅

[Pablito (Pawel Wozniak)]

Hi everyone!
As you may know in the latest Studio update we have delivered a possibility to export Studio’s telemetry data to your own Azure Application Insights instance. This data allows you to monitor and analyze what users are doing in Studio.

Steps required to set it up:

• configure your own Azure Application Insights instance
• configure Automation Ops on your tenant
  – create a policy and put the instrumentation key of your Insights instance to the Application Insights target section in the policy Feature Toggles tab.

Don’t forget about pushing the policy to the right target. You can do this by choosing the policy for the right level: Tenant, Groups or Users (you can read more about it here).

Using the exported data

After completing all of the steps above, your Azure Insights instance will start receiving events that you can consume by querying the database using the Kusto language in the Logs console. All of those events are part of the customEvents table.

Visualizing the collected data (Power BI dashboard example)

You can now visualize your data by building a useful dashboard. Such a dashboard could be produced with Power BI and its capability to directly link to the Azure kusto queries. This will drastically improve your company metrics and will help you monitor your development environment.

The main difficulty is that this requires writing a lot of queries, exporting them to PowerBI and then designing every single chart from scratch. To make things simpler, we prepared a sample dashboard that you will be able to easily import and save a lot of time. It consumes some basic telemetry events and converts them to neat charts based on your own data.

To get things going, we created a simple UiPath Studio project that will require simple input and will guide you through all the steps.

See this simple video that gives an overview of all the steps:

Example & content

The sample dashboard contains:

1. History of Studio sessions - date, username, the studio version, session duration.
2. User engagement - how many days a user was active in a month.
3. Timezone measurement - how many users work in which timezone.
4. Packages usage and activities usage - how many packages and activities were used recently and how many times.
5. History of package installation - when and who installed what and in which version.
6. Top 10 most used (installed) packages.
7. Projects history - consists of data related to projects like project name, project type, username and date.
8. Processes run history - who, from where a process was started.
9. A ratio of projects run between a local computer and the Orchestrator.
10. Projects created vs. projects published - see how many projects end up in the Orchestrator.
11. Projects published history - date, username, path and publish location.
12. Project published by a type - how many projects and which type were published recently.
13. “Run to this activity” feature statistics.
14. History of activities properties change.
15. Top 10 activities where a property was changed.

Below you might see an example of how the dashboard is looking like.

Additional Hint

The DataFlow file is by default set to query for data for the last 60 days. You can easily extend that by editing every table in the DataFlow file.

Project

Do not forget to grab a project that I described in the video
BI_DashboardCreate.zip (481.8 KB)

As always we are happy to help and we would like to know your opinion.

Let us know what do you think. We are waiting for feedback.
Cheers!

[Pablito (Pawel Wozniak)]

@MVP2021 - Guys I count on you to give it a try if you have a possibility.

[Pablito (Pawel Wozniak)]

HERE is the project that I forgot to attach initially (sorry for that).

[Radomir_Ivankovic]

This looks awesome, Ill give it a try.

[jtkc.geha]

this aligns or conflicts with UiPath insights?

[Pablito (Pawel Wozniak)]

UiPath Insights is mostly targeting business users and metrics are based on the Environment (Orchestrator) data at runtime/job.
The Dashboard I’m presenting here is available for everyone (Azure Application Insights Instance is required). It’s based on the Studio exposed data so apart from Insights you can measure data during the whole development process and control the usage, package installations, projects (even those that are not published yet etc.

[Viswas_V (211CT007 Viswas V)]

[Pablito (Pawel Wozniak)]

Hi Guys!
Has anybody tried it yet? Please share some thoughts. I’m really curious to listen to what do you think.

[Maidne (Nicholas P. Arnold)]

To build your own BI dashboard using the medal_sports data exported from Studio, follow these steps:

1. Prepare the Data: Ensure the exported data is clean and properly formatted (e.g., CSV, Excel). Check for any missing or inconsistent values.
2. Choose a BI Tool: Select a Business Intelligence (BI) tool like Tableau, Power BI, or Google Data Studio, depending on your preference.
3. Import Data: Upload the medal_sports dataset into the BI tool.
4. Create Visualizations: Use charts, tables, or graphs to visualize key metrics like total medals by country, medals by sport, or trends over time.
5. Customize the Dashboard: Add filters for sport types, countries, or years, and make it interactive by allowing users to drill down into specific data points.
6. Publish and Share: Once the dashboard is complete, publish it and share it with stakeholders.

This approach will help you create a comprehensive and user-friendly BI dashboard based on the medal_sports data.