Today, Tuesday, the 29.07.2025 – a date you may find in some datasets you work with. For you, it’s just a date: maybe you see a day, month, and year. Maybe from your perspective, it’s just a number. Maybe you remember the day, maybe not. It could be your birthday, it could have a meaning for you, or it was just a Tuesday in July that you don’t remember at all.
But in all cases, it is viewed from different perspectives. The program you use to analyze data also interprets the digits in different ways. For Excel, it might just be a number without points as dividers. Or it might format them as percentages, switch day and month, treat the value as plain text, or even return a number you don’t understand. But why so much talking about the date? The date field is a valuable field for different kinds of visualizations. And if that isn’t correct, your visualizations won’t be.
As there are many perspectives outside, there are also many data types inside the software. And for the software, the data type is important. If the data type isn’t correct, the outcome won’t be the expected one. I didn’t expect the 29.07.2025 to turn out the way it did, one of the last days in the Data School Training, and a real fail for me.
Our task today was to create a dataset and explain a formula or function in Power BI. I got the topics with different time functions. When I researched the topics one by one, I realized it wasn’t possible to build them the way I wanted in the short amount of time available. So, I started to make a basic explanation of the first topic. But first, I needed a dataset with columns and data fitting the topics I had to present. I went to https://www.mockaroo.com and created a dataset with Date, Sales, and various other columns with data to work with.
It isn’t that easy to create a dataset that makes total sense in a short time span. Some numbers weren’t perfect, but for a first attempt, it was fine.
I started with the built-in time functions YTD, QTD, and MTD and implemented the different measures. The topic wasn’t easy to understand, and I still hadn’t fully grasped it by the end, which I unfortunately realized during the presentation.
But there were further problems: when I started with the second topic, SAMEPERIODLASTYEAR and PARALLELPERIOD, I needed an extra table just for the Date, with all dates in one column. And in my case, that was a trap. After creating the table and connecting it, all my visualizations broke, and I could not fix them. So I had to start all over again and rebuild everything. I could not work with the data table, so I couldn’t continue with the further topics. On top of that, I ran out of time and still needed to practice for the presentation.
So the second day really didn’t go as I expected, and I didn’t have as much to present. Still, I am happy about it, because it wasn’t easy and not all days go the way I wish them to. Failing here and there is part of the process. Even when the feeling isn’t the best, aiming to make the best out of it is always a success.
Some days you win, and some days you learn. Today I learned a lot 😊. Especially realized that every other day of the training went pretty well for me, which makes me appreciate the good days even more. Thanks to the team and the coach, you are all great people!