171–180 of 387 posts
So I have to deal with both tools at my company. The reality is that it all feels so incomplete from a BI standpoint. Managers are throwing money at front end tools like Salesforce and Tableau, but the entire back end stack is still pretty much the same as 20-30 years ago (big expensive Oracle-ish databases). I think the development of Python and Jupyter and other less known things like Vega are much more interesting…
This seems really high for a company without earnings and a weird growth curve. Their ticker is cool and maybe sales force wants to be DATA on nasdaq. Otherwise, it will be hard to justify this high markup for a tool company. It will be awesome if Salesforce can adjust their model and make Tableau spit out D3. Their desktop tool is nice for designing, but their server components seem frequently unnecessary for runnin…
Tableau has a research division they themselves acquired recently in Boston.
However, 'Tableau Research' [2] has existed for years and its researchers regularly publish at major academic visualisation conferences like IEEE VIS (InfoVis/VAST) and EuroVis (see [3]).
[1]: https://www.geekwire.com/2018/tableau-acquires-mit-ai-spinof...
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I've seen that with retailers too-- but this is often driven by a fear/hate of Amazon rather than any real IT policy.
Yes, that seems more like Walmart/Target not wanting to support their main competitor in the retail space (Amazon) even though it's a different division.
Actually does Amazon's marketplace make any profit?
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Interestingly, I think an earlier version of the title had "in all-stock deal", but I think the mods removed it. I wish they hadn't, as that's an important detail for the reasons you mention. (Also, ask James Baker, who was convinced by Goldman Sachs to sell Dragon Naturally Speaking in an all-stock deal ... of a company that turned out to be the Belgian Enron.)
I was in speech recognition tech during that time. It all tanked, but Dragon got screwed the hardest. ScanSoft (now Nuance) made out like a bandit with all the tech fire sales post-bust.
If we look at Gartner's Analytics & BI magic quadrant from Feb 2019 ( https://www.qlik.com/us/-/media/B0DCF50C816448EEAC8981B02387... ) it becomes clear that Tableau(Salesforce) & PowerBI(Microsoft) are the driving force in the area. The move to buy Tableau likely comes from an interest in enhancing cross-compatibility between Salesforce+Tableau, the ability to provide a more robust service offering that can compete…
I’ve used PowerBI but it feels extremely limiting if you have a coder background. Don’t know a single person who likes the BI tools that exists today and I’ve worked with a lot of BI people. I’m convinced BI people becomes coders solely because of the bad tools that exists today. Intelligent autocompletion, git and strong types? No! But here, have some drag and drop!
Someone will come and build the dataset (or known as model) and the BA/DS can start building visualization that make sense to tell story about the company (or to tell the story about something).
It's a whole different market/profession.
So I have to deal with both tools at my company. The reality is that it all feels so incomplete from a BI standpoint. Managers are throwing money at front end tools like Salesforce and Tableau, but the entire back end stack is still pretty much the same as 20-30 years ago (big expensive Oracle-ish databases). I think the development of Python and Jupyter and other less known things like Vega are much more interesting…
> I think the development of Python and Jupyter and other less known things like Vega are much more interesting. In that case you may be interested in Dash (dash.plot.ly). It’s a free and open source library that you can use to create dashboards online with Python only.
Tableau feels more polished than PowerBI although BI has pretty much reached feature parity with Tableau.
The problem is the licensing costs. PowerBI is very affordable ($10 a month) while Tableau is not($70 and UP).
Tableau is basically saying, unless you have a corporation paying for the license err SAAS subscription do not bother to use us.
https://www.tableau.com/pricing/individual
There was a free option that was pitifuly unused and crippled to cloud only without any exports.
Then again by focusing only on companies for whom the licensing costs are a drop in a cloudy ocean Tableau brought in a 16B valuation.
One thing I've had to remind myself of - coming from a CS/Engineering background similar to most folks on HN (I'm guessing) - is that there are 2 types of people: Those who program and those who don't. To me, Salesforce looks like a big shared Excel file with a bunch of sheets. Tableau... well I can do the same thing with some scripts or spin up a web server. To others, this tech is just magical. Pay the money, do th…
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> the entire back end stack is still pretty much the same as 20-30 years ago (big expensive Oracle-ish databases). Other than the expensive part, is it really such a bad thing? I feel like relational databases are a pretty good fit for a wide set of use cases and have a huge amount of tooling.
The businesses are coming with requests that require complex SQL on millions of records of data that normally is sitting in various sources (warehouse, salesforce, etc.). Unless you hire expensive data engineers, you can't do this type of work reliably. You can stick things together with expensive GUI oriented prep tools like Alteryx, but you pay in reliability and, quite frankly, sleep. And forget IT, IT is so stuck…
So I have to deal with both tools at my company. The reality is that it all feels so incomplete from a BI standpoint. Managers are throwing money at front end tools like Salesforce and Tableau, but the entire back end stack is still pretty much the same as 20-30 years ago (big expensive Oracle-ish databases). I think the development of Python and Jupyter and other less known things like Vega are much more interesting…
Confused why you call SalesForce “front end”?