Transforming and visualising data using Power BI

The past two weeks I was introduced to the ins and outs of Power BI. Four full training days I’ve been practising doing transformations on columns, making calculated measures and dragging columns and measures into visualisations. For those who are not into data analyses, Power BI is a piece of software developed by Microsoft to handle data sets. When spreadsheets are no longer sufficient to handle your data, you can step up the game by using Power BI.

Before this training I practised with SQL and Python to create scatter plots and calculate summations, and I have to admit that after using Power BI I finally understand what kind of actions I was doing to data sets when using Python. Power BI is a visual tool, so you click on the transformations you need to do to prepare your data and the results are immediately visible. And you can easily undo a step with one click.

I wouldn’t say Power BI is data analysis for dummies, because you still need to know conceptually understand what you’re doing to the data, but I totally see why many people prefer using Power BI over messing about with Python. It is visual, quicker and can create interactive reports and dashboards. The reporting part is (for now) least interesting to me, as I don’t work in a big company with lots of (sales) data that needs to flow through the organisation. However, I do feel more confident after the past weeks that I’m capable to get meaningful information from data sets. And that was the whole point of investing in this course.