331–340 of 370 posts
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Qlikview costs quite a lot and I'd argue is also enterprise-grade, and doesn't have the same cost issue plaguing Tableau. Which is sad, because Tableau is probably the better product in many ways.
I am pretty sure Qlick deployments are way more expensive than Tableau ones because as far as I know it is more capable data modeling-wise. It is also nowhere near as polished.
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Most big companies are actually just fine with nonsensical results. It's a bit odd, but I've realized that nobody who uses BI actually cares much about data quality or integrity.
This. BI in large corporations is usually done by people having no clue about the data, producing bullshit results, leading to "insights" to management (who at that point have have no clue that all the cost columns were added up, regardless of currency), leading to a final "product strategy" that gets implemented over the next years, while in all the companies still producing innovation, this is usually done by a rog…
Certainly there are lots of bullshit metrics, there is often very little desire to audit data or even do a by hand sanity check once and a while.
That being said, there were _many_ engineers who actually gave a fuck about making sure we had telemetry in actionable, meaningful, and appropriate places, and unfrotunately the gap in analytics would take place far over their heads, when the upper management would produce documents with all the beautiful charts and graphs, communicating.... absolutely nothing.
Graphs with mixed axis scaling (log vs non log) graphs with mixed units, conclusions that are a total stretch from the data that's there and ignoring obvious conclusions that don't line up with what the managers want to say.
For there to be USEFUL BI (and such a thing certainly can exist) there needs to be a "this isn't bullshit" mindset up and down the whole stack, not just in engineer land.
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Tableau is a surprisingly good desktop application for business intelligence and analytics that, IMO, grew too big for its own good. You plug it into data (spreadsheets, databases, you name it) and it makes it very simple (drag-and-drop simple) to crunch some numbers and produce interesting graphs, visualizations and analysis. Some clever stuff they had was (early-RoR-style) guessing of data semantics based on heuris…
I used to work at a company where, under duress, I had to push tableau to its limits. My company spent hundreds of thousands of dollars on it. The main use was to provide reports on the data created by the application we sold. It would be great if it just stayed as a better version of the excel chart maker. Instead, it was seen in my company as a way to replace programmers. All of these types of applications have the…
- Beyond simple queries, it becomes more easier to setup a view or two behind Tableau than to do it purely in Tableau. E.g. multiple level of latest times, more complex aggregations etc are more easily done in SQL than via Tableau.
- For some things Tableau doesn't do what we typically expect. Couple of examples:
- If you run a custom query joining two tables with some of the column names being same in both, Tableau cannot deal with it. Setting alias for columns using "as" works fine in SQL so I think it is not unreasonable to expect that to work.
- I recently tried to chart lag in request/response in microseconds. The data is stored as TIMESTAMP in our Vertica database. However, I found that Tableau doesn't show time more granular than seconds. That is kind of odd in today's common low-latency high-performance technology environment
Having said that, I really like the features it offers viz. Calculated fields which don't go away just because I change the data source, drag-and-drop dashboard constructions, very nice visualizations etc.
I use Tableau almost daily. Initially I found it harder to work with and avoided it for a while. On 2nd attempt, for some reason, everything clicked into place and I now find it fairly intuitive. Some of my opinions/experiences about it: - Beyond simple queries, it becomes more easier to setup a view or two behind Tableau than to do it purely in Tableau. E.g. multiple level of latest times, more complex aggregations…
If it's for analysis why not use python or R, way more powerful and full of tools & libraries that give you speed you need?
If it's for reporting, why not to use chartio, looker or anything that connects directly to your db?
My opinion: If you know some python or R, you might still need chartio, looker and similar but Tableau doesn't make sense anymore.
I use Tableau almost daily. Initially I found it harder to work with and avoided it for a while. On 2nd attempt, for some reason, everything clicked into place and I now find it fairly intuitive. Some of my opinions/experiences about it: - Beyond simple queries, it becomes more easier to setup a view or two behind Tableau than to do it purely in Tableau. E.g. multiple level of latest times, more complex aggregations…
What do you use it for? If it's for analysis why not use python or R, way more powerful and full of tools & libraries that give you speed you need? If it's for reporting, why not to use chartio, looker or anything that connects directly to your db? My opinion: If you know some python or R, you might still need chartio, looker and similar but Tableau doesn't make sense anymore.
Reporting --> Chartio, Sisense, Looker etc. (anything web focused without a desktop version pretty much) Analysis --> Ipython No room for Tableau and similar.
Tableau makes most straightforward analyses much simpler than attempting to do it in Ipython/pandas, especially when connecting to standard corporate data warehouses (probably on the order of 10x faster). Of course you quickly hit a ceiling in terms of complexity, but most analysts never really get to that point.
For ad hoc analysis instead, there is really nothing more powerful than R or python and it's plenty of tools & libraries that give you the speed you need.
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What do you use it for? If it's for analysis why not use python or R, way more powerful and full of tools & libraries that give you speed you need? If it's for reporting, why not to use chartio, looker or anything that connects directly to your db? My opinion: If you know some python or R, you might still need chartio, looker and similar but Tableau doesn't make sense anymore.
I wasn't part of the decision making effort but I believe Qikview was also considered but the analysts preferred Tableau. It is used by the analysts as well our for our internal monitoring/charting/analysis purposes.
For reporting the idea of transforming & moving the data around really doesn't make much sense when compared to solutions which directly leverage your db or at least create an unique consistent datasource instead of many so-called extracts scattered around.
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Honestly I have never used anything similar to Tableau in the balance of "straight-forwardness" and quality of results. My use case is: here's some data, let's take a look at it and make some decent graphs including any sort of comparative analysis. Excel is... well, Excel. The kitchen sink bundled in it contains pivot tables. Graphs are hideous out of the box, and very limited. Apple Numbers makes cute looking graph…
> And I have to put stuff in SQL and do the plumbing if I need any meaningful preprocessing. Actually, the plumbing isn't as difficult as most people make it out to be. Nowadays, its the era of abstraction and FOSS infrastructure tools like jQuery, Bootstrap and like you mentioned, Highcharts. I'm a freelancer who quite recently developed a Tableau replacement for one of my clients. This client realized that all he b…
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I don't think enough people have tried Shiny. It is fantastic and super easy. People really assume it is very difficult to get a grasp of.
Yeah I agree. We moved our visualizations from an expensive SaaS product to a few page Shiny metrics app that costs almost nothing.