You can't beat Tableau for this sort of task if you're not technically inclined and if you are then you can't beat Shiny. Both offer better and more customizable results. I wonder what the added value of this software is.
It's quite convenient for those of us who already have the relevant data inside Google Cloud Platform (specifically BigQuery for me). I've made a few dashboard/graph-type things in Google Data Studio and they were super simple to set up and powerful enough for my use case.
I had major problems getting AdWords custom columns working in here which was a deal breaker for me. Too bad since I'd expect AdWords to be fully supported, but then again custom columns aren't really first class citizens in AdWords yet :(
Tableau is great but is also pricey. I like that it can be on-prem which is a nice feature most saas players can't match. They have drivers for tons of sources.
Zoomdata is a good alternative, but pricey and not mature enough I feel.
PowerBI is getting surprisingly good, and if you're a Microsoft or R shop it can be a really nice fit for the price. I've thrown a few 50GB+ CSVs at it. It's basically Excel on steroids. If you're dealing with some data stores (like mongo, elasticsearch) then PowerBI isn't viable natively.
Interesting to note that zoomdata and tableau use spark under the covers iirc.
You're right that we don't use Spark as our data engine, but we also don't use hyper yet either (well, we do in beta[0] :). Hyper is replacing our existing data engine (conveniently named "Data Engine" [1])
Yeah you're right about spark for the processing. I did see a lot of Hadoop binaries in their tableau server (it amused me to see zookeeper.exe in windows task manager) and assumed they were using spark for internal data representation, but that was a false assumption I suppose.
Like Tableau and Shiny it looks great for reports and presentations, but what would you know to get the hang of a new dataset? To visualize some descritive statistics, spot outliers, see missing data?
Maybe it is better to use Python Pandas or R interactively to know more about your data.
Check out my EasyMorph (http://easymorph.com). It's a hybrid between data prep and ETL -- you manipulate data interactively, yet it can work as an automated workflow. You can even build custom data profilers with it, tailored to your particular metrics of interest.
What does Tableau still have over Microsoft Power BI at this point?
In the beginning Power BI started out pretty weak compared to Tableau, but over a couple years they make huge investments and seem to even be ahead in some areas. For example, it used to be Tableau didn’t support 3rd party or custom visualization, although I haven’t checked recently if that’s changed.
So much development effort is being poured into many of these competitors, any useful comparators have to be pretty new.
Looking at the Gartner report posted above[0], it appears that Power BI has problems with data volumes, support, and (IMO the biggest issue) is it's cloud-only. For some businesses, e.g. healthcare, the lack of an on-premise solution may be a showstopper.
