plotly is awesome. A lot of companies spending $50k + a year on BI software can do better (and save a ton of money) by throwing plotly iframes on some simple static webpage and update them at any interval using cron jobs and python.
The cost of any BI project is dominated by the time and effort put into ETL and data modelling. 80% of our effort goes toward this back end work. With this in mind, the presentation layer is essentially an afterthought. The lion's share of BI cost goes to expensive humans. If you can spend a few $100Ks for presentation tools that integrate seamlessly with the back-end analysis services and streamline report design/publication, then it's a no-brainer.
With technical employees/consultants at a premium, and in short supply (especially in the data modeling space), it is worth $100Ks annually to have a toolset that allows non- and minimally-technical employees to quickly and easily build new reports.
Take a look at Microsoft's PowerBI dashboards, or at the visualization capabilities in Tableau. The functionality there is what businesses want/need.
Those tools and Plotly equally require a solid data warehouse behind them to support any meaningful and timely analysis. The marginal cost of a highly-integrated and easy-for-non-technical-resources reporting layer is pretty low after that investment.
Been there, done that.
This is the mantra of the BI system marketing machine that I've never actually seen work in practice.
But I'm glad you've seen BI enterprise systems succeed where the end users are happy and feel their toolset is flexible enough for the new daily challenges they encounter (sincerely).
I love Tableau as an exploration tool and think the UX and visualization capabilities are awesome. Just not the solution end users wanted. I've also rolled out a massive cloud based enterprise BI system (data warehousing, ETL, etc.) at a separate company. That wasn't the solution, either. Plotly was. But, just my two cents.
You're definitely right that none of the enterprise solutions are completely "there."
It still seems to me that "Export to Excel" is the strongest BI feature of any tool. Pivot tables are ubiquitous. Throw any OLAP cube up on a server and host a workbook on SharePoint and you're probably 60% of the way to a good BI ecosystem.
^^ This is in terms of data vis and presentation ^^ The backend work still dominates.
Fair disclosure: my company is a Microsoft Partner, so my primary exposure and all of my work is in that ecosystem. For geek-cred, I run Arch and OpenBSD for all my personal systems.
One physics postgrad + pandas + hdf5 + tableau (via csv) + angularjs + flask = big data done on the cheap.
2h query on Sybase -> response under a second.