Power BI is a great analytics tool, but why do we need it?
This article explains why Power BI is such a useful tool for data analytics and how it compares to Excel. We’ll start with a quick example about a simple grocery store owner and his data.
Alan’s Grocery Store
Meet Alan, a local grocery store owner who uses Excel to track his monthly sales.
Excel works great for high level use cases like this, and it’s very simple for Alan to use. However, he now wants to dig deeper to see how specific departments and items are trending.
To do this, he needs to connect to his raw sales data, where the cash register logs all of the sales transactions to a relational database in the back end. However, with thousands of customers per day, this database grows to have millions of records in it, which is too much data for Excel to handle.
One alternative is for Alan to aggregate the data in a SQL query and export the summarized data to Excel. However, it takes a lot of time and effort to learn the SQL syntax, and he’d have to update and re-run the query every time he wants to change a filter or refresh the data.
This is where Power BI comes in handy.
Power BI to the Rescue
Power BI provides a nice “drag and drop” user interface for connecting to databases, aggregating data, and visualizing results. The final product is an interactive dashboard of visuals that can be filtered with the click of a button.
It’s very similar to Excel in terms of ease of use (i.e. a business owner like Alan can learn to use it relatively easily) but connects directly to databases to handle larger volumes of data.
There’s also an online service where Alan can publish finished dashboards for others in his business to see. The data can be scheduled to refresh automatically, allowing Alan to basically “set it and forget it” instead of manually refreshing every time he needs it updated.
To sum it all up, we made this little chart comparing all 3 of Alan’s options:
With all these capabilities, Power BI has taken off in the analytics world, and it’s one of our core tools here at Daily Data.
More Use Cases
You can check out another Power BI use case in our Fantasy Basketball Optimization series, where we created a report to analyze performance metrics for our fantasy basketball team. The report gave us a lot of insights through a variety of different interactive visuals, including
- Single game vs locked averages by player
- Lock-in bias percentage by player/position
- Overall team performance over time
With the help of our Power BI report, we even went on to win the league championship!
You can see a more in-depth explanation of this along with source file downloads from our Exploratory Analysis in Power BI post in the series.
Conclusion
While Excel is a common tool for a lot of simple data analysis, it doesn’t do well with larger datasets and databases. Tools like SQL can be used to aggregate the data straight from the database, but they have a steep learning curve for non-technical users.
To help with this, Power BI was created as a “drag and drop” solution for easily aggregating and visualizing data. It also provides capabilities for sharing automated dashboards of interactive visuals, eliminating the need for manually refreshing and sending out files.
Got any ideas on how you could use it? Feel free to drop a comment below.
We hope you learned something today, and we’ll see you next time!