“Power BI is a business analytics service that delivers insights to enable fast, informed decisions.” – Microsoft
One third of the Microsoft Power Platform, Power BI quickly transforms data into rich visuals. If you were a fan of Power Query, Power Pivot, and Power View in Excel, then this should feel familiar…
To recreate this example, you will need:
- Power BI Desktop
- *or a license for the web portal*
- Export of your Netflix Viewing History
Note:
The Netflix Viewing History is exported to a CSV with two columns: Title and Date.
Open Power BI > Get data > Text/CSV
Once the data is loaded into Power BI, toggle to the Data view and click Modeling in the ribbon. This is an optional step, but just because, I added three new columns: Year, Month, and Quarter.
- Year = ‘NetflixViewingHistory'[Date].[Year]
- Month = ‘NetflixViewingHistory'[Date].[Month]
- Quarter = ‘NetflixViewingHistory'[Date].[Quarter]
Interesting feature of Power BI is that it will try to figure out your data column types. If the data looks like GPS coordinates, then it’ll assume the column represents a location. However, if it can’t determine the type, then it may just list it as Uncategorized.
Building a Visual:
- Select the Stacked column chart visualization.
- Drag Year, Quarter, and Month to the Axis section.
- Drag Title to the Value section.
End result, a bar chart showing a year-to-year trend of total things watched. Power BI tip, you can right-click and Drill down into a specific year, then a specific quarter, then a specific month…
Sample: year-to-year totals
Sample: yearly counts broken down by quarters
Bonus #1:
Drag Month to the Legend and you’ll create a true stacked chart.
Bonus #2:
Swap the visual for ‘Ribbon chart’ for an artistic expression…
Conclusion:
Power BI is powerful enough to create plenty of visuals and your data can come from plenty of data sources, but Text/CSV may be the easiest to test. Experiment with the data sources and explore the visuals…
“The unexamined life is not worth living.”
Socrates
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