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Power BI on Magicline's Enterprise Data Warehouse

A showcase on reports that can be built with Power BI Desktop connected to Magicline's Enterprise Data Warehouse. See documentation of Enterprise Data Warehouse for more information.

Get started

  1. Download the showcase report template (or any other .pbit file).
  2. Run using Power BI Desktop.
  3. On opening a warning is displayed, that is due to a parameterized connection setting and can be safely ignored. Click OK.
    Ignorable Potential security risk
  4. Enter server and database with the redshift connection information we provided to you. Please make sure you are connecting using the static IP address you provided to us!
  5. Enter user and password with the Redshift connection information we provided to you.
  6. The tables should now be loading and you can explore the showcased reports!

Note: All tables are set up using "Direct Query". But this is not required and you can adapt settings and switch their loading mechanism as you wish.

Showcase

Revenue

The sum of net accrued revenue by year_month and studio name, that was made in the past year. Revenue Stacked Bar Chart

Checkins

The count of checkins by checkin_date and studio name, that happened in the previous 3 months. Checkin Count Line Chart

Active Contracts

The count of contracts active (started and not ended yet) in a particular month. By year_month, studio name and type of contract. Active Contract Count Stacked Bar Chart

Contract Cancelations

The count of contract cancelations at their cancelation date. By year_month and studio name. Contract Cancellation Count Line Chart

Payment Run Amount

The sum of amount in payment runs in the previous 3 months. By year_month and booking type. Payment Run Amount Stacked Bar Chart

Class Events

The count of class (booking) events in the previous 2 months. By year_month, class event status and studio name. Class Event Booking Count Stacked Bar Chart

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A showcase on reports that can be built with Power BI Desktop connected to Magiclines Enterprise Data Warehouse.

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