PowerBI on the other hand is a straight up dashboarding tool. I've used it and it isn't quite as powerful as Tableau, but it's an easier step up from Excel. It doesn't require you reorient your mindset as much as Tableau does. But it also doesn't let you probe your data as easily as Tableau does. It's essentially a supercharged Excel dashboarding tool
Excel viz is rudimentary. It gets the job done for simple plots, but it's a hassle to join data (you have to do cell VLOOKUPs or INDEX(MATCH())) and pivot tables are a poor-man's approximation of the true power of SQL operations. It doesn't scale to large datasets but the cell-based spreadsheet paradigm (vs. a relational database paradigm) is easy to understand which has an appeal of its own. But you're ultimately limited to what fits on a spreadsheet.
Tableau is really amazing actually.
PowerBI?
Apache Superset? https://superset.apache.org
Are there some videos that walk a user through setting it up to using it?
[0] https://datastation.multiprocess.io/docs/
[1] https://www.youtube.com/channel/UCGOQFKonPUVo5LgxQDW26yg/vid...
On the other hand, Redash has served my startup really well for the first 3 years (and now we're finally moving to Tableau)
I have used Vega + Jupyter a few times. As well as the Vega Viewer extension for VS Code. I haven't used it enough to be proficient and fast, but I have used it enough to know that I want to be.
Pandas is better but requires programming.
Tableau is fine for what it is, but I've found that the requests from stakeholders often grow to a point where you either can't do it in Tableau or have to move mountains to get it to work... so, in essence, sunk cost fallacy makes tableau millions.
I still refuse to learn pandas enough to replace dplyr though, as it's just so painful to use the API compared to how easy this stuff is in R.
This is a popular opinion, in my book.
The backstory was a large BI team having no proper tools for reporting, except maybe Looker for tabular KPI reports. So any addition of Tableau was an all our nothing buy, every single analyst or whoever on the BI team needed a seat, even though most of them wouldn't ever use it. For that matter 95 percent of the BI team would never move away from Excel. Anyway, the costs were huge for something that should have been a leap in capabilities.
Also, it always struck me as something too complex for the non-technical folks, and not expressive enough for tech-literate analysts/data engineers &c.
That's more than an equally domain specific process like Qlik, and more than a specific vendor tool like tableau. And anyway if PowerBI didn't have a pain point it wouldn't be a MS product.
"Connect to an arbitrary database, create a view that joins numerous tables (including foreign tables, via blending) together, load to columnar storage on a local SSD for performance if necessary, add arbitrary derived columns (including well-defined lateral lookups for things like 'annotate this action with the date of the first action of this action's user' [0]), group by 4 of the derived columns, map two of the groupings to nested dimensions along the horizontal axis and two to the vertical axis, and show the sum or count at each cell in a resulting table, then when satisfied, drill down into a slice and turn it into a bar chart with colors that match your branding needs" - every one of those clauses can be accomplished with drag-and-drop mouse commands almost at the speed of thought.
And once you get the hang of it, there's zero impedance mismatch with hand-rolled SQL, it's just way faster to iterate on, especially with schemas where you may not remember all the columns available to you, and especially when you're doing so over screenshare with non-technical colleagues.
[0] https://help.tableau.com/current/pro/desktop/en-us/calculati...