Power BI is becoming increasingly prevalent in HE as a tool for creating visualisations and drawing insights from timetables, attendance data, room lists, and other university datasets.
But unlike Excel, which is a more general-purpose tool, academics oftentimes have less hands-on experience with Power BI, given its more specialised functionality.
We thought we would share some useful features for interacting with your data which you may not have come across yet.
But unlike Excel, which is a more general-purpose tool, academics oftentimes have less hands-on experience with Power BI, given its more specialised functionality.
We thought we would share some useful features for interacting with your data which you may not have come across yet.
📈 Export data & show as a table

Show as a table is another self-explanatory option that strips a visual down to the tabular data behind it. Graphs are great, but it’s sometimes easier when investigating data to see only the values themselves. These tables preserve the sorting of the visual (chosen in the Sort axis option from the same menu).
👷 Drill up & drill down
Data hierarchy refers to the structure in which data is stored, composed of categories and subcategories of increasing granularity. Some familiar hierarchies include:
- Academic Year > Semester > Teaching Week > Day > Time
- Department > Module > Activity
- Campus > Building > Room
🡡 To drill up means to move up in the hierarchy, aggregating data to get a broader understanding of its trend.
🡣 When drilling down, you can do so in three ways:
- Choose a specific element within a category to expand into.
e.g. View Tuesday’s data split by time. - Move down to the next level in the hierarchy.
e.g. View all the data split by time. - Expand all down one level.
e.g. View all the data split by both day and time.

🤖 Q&A
This feature is powered by AI and effectively lets you speak to your data. Instead of scouring through tables or busting out a calculator to get the results you need, why not ask this robot to do it for you? (You don’t even need to be polite.)
Give me total booked hours by department in bar chart
Which activity type has highest average attendance rate?
Top 3 buildings in main campus by number of rooms
Provided the relevant columns and measures already exist in your dataset, this can be the fastest way to retrieve a certain data point or temporarily visualise a distribution for your analysis.
How do you use Power BI within your institution?