Blog with real world examples of Excel spreadsheets for work (e.g. timesheet) and sports (e.g. analysis of results of 10K races). And blog has also examples made with other Business Intelligence tools as MS Power BI and Google Sheets and Google Data Studio.
#95 Power BI dashboard Messi Goals Tracker with new PBIP and PBIR file format
In 2026, the new Power BI default file format will be PBIR (JSON text format), which facilitates version control. NB: for more details about this, see e.g.:
I wanted to try this out, so I made a new Messi Goals Tracker dashboard, using the PBIP (Power BI project) file format, that includes a PBIR-file for the report part, and a TMDL-file for the semantic model part. NB: for earlier versions of Messi Goals Tracker dashboards, which I made with Google Looker Studio and Tableau, see these posts:
And here is a video that I made about the dashboard:
This video shows a ´master class´penalty goal that Messi made in 2025 with Inter Miami. And in this video you can see another, very special, penalty goal which Messi/Suarez made for Barcelona in 2016, in a way Cruyff did for Ajax in 1982 (also included in the video).
For version-control, I use the Git-functionality in MS Visual Studio Code. A nice feature it has that with Copilot, you can generate the content for the commits.
Here an example of a measure that I added to the Semantic Model in Power BI and the traces of this in Visual Code and GitHub:
And here you can see the PBIR-file with the code of the Info-page in the Power BI report:
If you enjoyed this post and want to make a small donation, you can do this with the Paypal Donate button (at the top right of this post) or via BuyMeAcoffee .
#93 Power BI report ´Big 3 of Tennis´ with qualitative data and the Power BI custom visual Card Browser
The other day, a friend asked me if I could help with a dashboard for his work that should facilitate data-exploration of the results of a survey, which had just qualitative data. So the dashboard was not supposed to be the typical ´pivot-table dashboard´ with measures, so quantitive data (e.g. sales) and some dimensions (e.g. Product, Customer, Date), but more a ´Power Point interactive dashboard´.
I checked on the web if there were examples of Power BI dashboards with qualitative data, and found this:
This dashboard is made by DiscoverEI , that converted a 107 pages (e-)book into an interactive Power BI report. As they say:
"Power BI is not just limited to visualising quantitative data, it is also a fantastic data storytelling tool for transforming large amounts of text (qualitative data) into an interactive dashboard"
Another intersting example of this, is the (public) dashboard they made for the project ´Environmental Data Storytelling - Gippsland Water's Urban Water Strategy´:
In their dashboard, I saw the Card Browser Power BI custom visual which I thought could be interesting to use into the prototype dashboard for my friend.
First I created with ChatGPT the dataset for my report, so with some properties of the ´Big 3 of Tennis´, Federer, Nadal and Djokovic, e.g. favourite surface (clay, grass, hardcourt), left/right handed, playing-style (baseline, all court) etc. Then I made the Power BI report for this data, so using the Card Browser visual:
And in animated gif format:
NB: the data of this report is correct for Federer (retired in 2022) and Nadal (retired in 2024), but a bit outdated for Djokovic, who is still active and has now (Sept. 2025) 100 ATP titles, making hem part of the group of 3 tennis players with 100(+) ATP-titles, with Federer (103 titles) and Conners (109 titles)
And for a (longer) video with a demo of this dashboard, see:
NB: at the end of my video, there is a fragment of the match:
Rafael Nadal vs Roger Federer - Battle of Surfaces 2007, an exhibition match where half of the court was of clay (the favourite surface of Nadal) and the other half was of grass (the favourite surface of Federer) , source:
https://fightagainstcorruption.eu/Dashboard - Dashboard with anti-aorruption practices in the EU, as described in ´Handbook of good practices in the fight against corruption´.
For these dashboards, a lot of attention was paid to the design of the user interface, and in this video of Greg Deckler, you can learn more about the UX-design work for a Power BI report, for which he uses in this very nice dashboard:
If you enjoyed this post and want to make a small donation, you can do this with the Paypal Donate button (at the top right of this post) or via BuyMeAcoffee .
#90 Power BI dashboard Rafael Nadal's Grand Slam tournament finals in whole career (2001-2024)
Recently Rafael Nadal, one of the GOATs of tennis, announced that he will retire (at age 38). His last tournament will be the Davis Cup in Nov.2024 in Malaga (Spain).
In 2014, I made an infographic (in MS Excel) about Nadal's win/loss records, see this blog-post. And now, 10 years later, at the end of Nadal's career, I made a dashboard with MS Power BI, with the result of all Nadal's Grand Slam finals (#30) in his 23 years-career (2001-2024), finals that he played between 2005 (when he won his 1st Grand Slam tournament, at age 19) and 2022.
NB: The embedded version of this Power BI dashboard, you can find at the bottom of this post.
The dashboard is interactive, e.g. you can filter on all Nadal's Grand Slam wins (22):
Or you can 'drill-through' from a chart in the dashboard to the table with the underlying details, e.g. in chart "Finals by Tournament and Result", for tournament = 'French Open' :
And this is the complete table, so with all Nadal's Grand Slam finals:
*FACT 1: Grand Slam finals played by Nadal: 30, wins: 22, losses: 8
*FACT 2: Nadal played 9 finals against Roger Federer. And the other opponent he met often (also 9x) in a final was Novak Djokovic (who has 24 Grand Slam titles until now, so 2 more than Nadal). Here the chart with the win/loss details of Nadals finals against these other 2 tennis-GOATs, in Spotlight-mode:
*FACT 3: Nadal played and won 14 finals of the French Open (Roland Garros), which is played on clay, his favorite surface. No other winner of the French Open comes close to this. Bjorn Borg is 2nd in the Roland Garros-winners ranking, with 6 wins, as this chart generated by ChatGPT shows:
NB: this is the Python-code of ChatGPT's analysis:
And ChatGPT gave also this other fact about Nadal's 14 Roland Garros wins:
*FACT 4: 2010 was Nadal's best Grand Slam year: he played 3 finals (French Open, US Open and Wimbledon), and won all 3. NB: I added a (special) custom tooltip to chart "Finals by Year and Result", so that you can see more details of these finals:
(Page 2 of dashboard)
*FACT 5: Of the 14 finals of the French Open that Nadal played, most were against Federer: 4 finals
*FACT 6: Nadal played against Djokovic in the finals of all 4 Grand Slam tournaments, in total 9 finals (wins: 5, losses: 4): -French Open, wins: 3 -US Open, wins: 2, losses: 1 -Australian Open: losses: 2 -Wimbledon: losses: 1
*FACT 7: Nadal won all 4 Grand Slam tournaments in his career. He reached this 'career Grand Slam' in 2010:
*FACT 8: What is maybe not so easy to see in my Power BI dashboard about Nadal, is the fact that there were 3 years that Nadal did not play any Grand Slam final: in 2015 and 2016 (after having played in the previous 14 years at least 1 Grand Slam final each year) and in 2021. I made another dashboard where I enriched the data from the original Wikipedia-datasource with these 3 years:
NB: This post explains more about the reason why in 2015-2016 Nadal had a weak period:
But Nadal came back, and won again 4 years in a row: in 2017-2020 6 Grand Slams and 2 more in 2022.
When I saw that ChatGPT could make the Roland Garros winners chart (see FACT 3 above), I was wondering if it could also create a dashboard with multiple charts:
But Power BI can auto-generate a report/dashboard (using built-in AI), and here you can see the result for my Nadal-dataset, where I marked with green the charts that I think are useful (and with red those charts that are not).
So I think this proves that AI can't replace a (human) data-analyst. I also asked ChatGPT about this:
I wanted to see how good Power BI's AI feature 'autocreate report' was, but I was disappointed, it looks to take some random permutations of the different attributes to slice the measure, I guess because it doesn't know about the underlying concepts, as a human does, is this true?
And here's GPT's answer:
And I also liked GPT's alternative response, which includes this:
I used GPT also for a review of my Power BI dashboard, for which I made a screenshot of the dashboard and attached this file in my prompt ('please review my dashboard, see attached file'):
Even though Nadal will stop with tennis soon, the future of Spanish tennis looks bright with Carlos Alcaraz, who already won 4 Grand Slams at the age of 21, and of which Nadal said: "he's going to be one of the best in history" (see this post). I asked GPT to plot a chart with Nadal's and Alcaraz's number of Grand Slams per age, here the result (after some iterations/mistakes by GPT):
I hope that Nadal will play in the Davis Cup and that he's in a good shape (no injuries..), and it would be very nice if Nadal and Alcaraz would play together in the double.
If you enjoyed this post and want to make a small donation, you
can do this with the Paypal Donate button (at the top right of this blog-post) or via BuyMeAcoffee .
#89 PowerBI-report UEFA Champions League Titles by Team, history (seasons 1955-56 to 2023-24, winner: Real Madrid)
On 1/6/2024, Real Madrid won the UEFA Champions League (UCL) final from Borussia Dortmund, and with this its 15th UCL-title (!).
I made a Power BI dashboard with all teams that won the UCL (before 1992 called European Cup), from the first season, 1955-56 until now (season 2023-24), here some screenshots. NB: at the bottom of this blog-post I included the dashboard (embedded, interactive version) + download-URL.
With filter on Country = Netherlands (country #4 in ranking #UCL-victories per country):
You can do a drill-through for Real Madrid (-bar) to see the details of all Real Madrid's UCL-victories:
To see how Real Madrid got to these 15 UCL-titles over time, I made a chart with the cumulative # titles. In this chart you can see e.g. that Real Madrid won the first 5 UCL-finales in a row (with Real Madrid -legend Di Stefano).
NB: The DAX-formula for measure cumulative # titles, I got with help from ChatGPT:
With this decomposition tree chart, you can see a breakdown of the 15 UCL-titles, where I chose the path: Country (Spain) > Team (Real Madrid) > Coach (Ancelotti, trainer with most UCL-victories, total 5, 3 with Real Madrid and 2 with AC Milan) and Season/Year (2023-24)
To make a Power BI dashboard as this, normally I'd search for the dataset on internet, e.g. Wikipedia, and then transform the dataset for my reporting-needs (e.g. in Power Query). But now there are generative AI tools/chatbots as OpenAI's ChatGPT, which I used, that can create the dataset you want, or close to it. For the dataset that ChatGPT generated for me, it missed data for UCL season 2023-24, because ChatGPT has a cutoff date of Jan.2022, so the data for that season I had to add manually. ChatGPT created some Python-code for the dataset, which can be loaded in Power BI (as it also told me):
I also asked ChatGPT which visual it would recommend for this data, and it even draw the chart itself (something that was not possible with ChatGPT 3.5, but now with ChatGPT 4o it is):
So these new AI-tools can make the life of a data-analyst and data-journalism work as I did for this post much easier, until one day we are not needed anymore..
If you enjoyed this post and want to make a small donation, you can do this with the Paypal Donate button (at the top right of this post) or via BuyMeAcoffee .
