Some clever stuff they had was (early-RoR-style) guessing of data semantics based on heuristics (Column labeled "date"? probably worth grouping by months. Number pairs like -0.3242,0.12345 ? probably worth plotting on a map).
I have used trial and educational versions in the past and was always pretty impressed with the ease of use and the results. The product itself was > $1k so I never actually purchased a license.
Even though I didn't follow the strategy very closely, from what I've run into it seems lke their offerings were all over the place. I saw a local newspaper using a hosted Tableau product to display data visualizations on their pages (the kind of visualizations made by a company whose DNA is desktop apps, so kind of underwhelming). Their website is all about Gartner and enterprisey lingo.
The product itself is, well, some advanced version of Excel. This means you either sell a lot of it very cheap, or very little of it for a lot of money. Website design suggests the latter. Too bad it seems to not be working.
I'm honestly sad to see them do badly as I think the product was really innovative and it really changed my way of thinking about report building and analytics tools.
Tableau is more differentiated than it looks, but it doesn't look very differentiated. If Microsoft ever gets around to making many of the "smart" features in Excel actually work (i.e. csv import and automatically choosing what kind of graph to make) they will have nothing to stand on.
I'm just waiting for the street to realize that Hortonworks and their competitors also have zero moat, and if anything, a GUI interface for a Hadoop cluster is value subtraction in the age of devops.
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 graphs, but is extremely basic.
Viz toolkits in JS make you code for stuff that should be straightforward, at different levels of abstraction (Highcharts -> D3). And I have to put stuff in SQL and do the plumbing if I need any meaningful preprocessing.
Self-proclaimed "business intelligence" tools don't really target this use case. They solve enterprise problems like connecting to MDX sources that are not there for me.
Do you know any other tools for this?
I've spent too much time watching people spend months and tens of thousands trying to bend 12 different third party tools together when a developer could do the whole thing in a week and it would actually do what you want it to do.
Nailing down the actual requirements is the hard part of building your own dashboard, it sounds like you've done that. If your needs are stable-ish or you have consistent developer resources it's going to be hard to find a better fit than that.
It's for when you want to figure out what the data is telling you, and not how to wrangle the data into saying something.
In 99% cases, that happens because your requirements change. If you hire a competent developer, the total cost of development is always a pittance compared to what you pay monthly/quarterly to a product based company.
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 basically wanted from tableau was a chart and some basic data manipulation like sorting, filtering and grouping (count, sum, average, etc.). All the things needed to develop this little app already existed in the FOSS world:
1. Highcharts/jqplot for charting.
2. Twitter-Bootstrap for showing a professional front-page and UI elements.
3. jQuery and jQuery-ui for DOM manipulation, AJAX handling for SQL queries, enabling drag/drop, etc.
4. PHP/Mysql on the backend (which is needed in anycase).
As for plumbing, each of these tools is so well-documented and also a simple Google search will point to tons of StackOverflow links that happily provide an answer to any and every question you may have!
tldr; Library/Framework plumbing might seem complex initially, but for a practiced Web-Developer, its like a cake-walk!
Disclaimer: I work for Microsoft.
https://ideas.powerbi.com/forums/265200-power-bi-ideas/sugge...
The free desktop version is not limited. It's very powerful. The growth rate is astounding. We get significant new features every month, sometimes weekly.
If you compared PowerBI to Tableau 6 months ago (or even 3 months ago) you are out of date. Its data model capability is far superior to Tableau. The formatting and graphics capability is catching up quickly. The intuitive UX is first rate.
(We are NOT Microsoft employees.)
In the BI market, Tableau is very much one of the low-cost, high volume players. They've done a great job getting into lots of people's hands, the question has always been whether or not they can roll the volume of cheap(ish) single user licenses into large enterprise-type deals.
The problem for us is that as a consulting house, our staff turnover rate is high (as expected I suppose), and this doesn't work well with Tableau's named license model. We've run into troubles where we reassigned licenses after people either left projects using Tableau, or left our company altogether. They ended up forcing us to buy extra licenses, which I was unhappy with.
My stance since then has been to avoid buying more licenses. We're getting our team skilled up more on web-based viz, so we can reduce our dependence on desktop applications.
The one thing that I like about Tableau is that its documents are XML, which plays nice with git.
I was working on a project where the client wanted to use Tableau and I pushed instead for Shiny, which is the way we went. Quite happy with the decision.
Most of our clients are tier 1, so in some instances they already have heavy investment in Qlik, but some are willing to shell out cash for Tableau where it makes sense. I've seen senior management in clients complain about the price though at times.
However, one needs to do the analysis to create a worthwhile dashboard anyway and the report can be generated easily with the knitr package.
Anecdotal, but I've seen this happen several times with clients who previously used Tableau.
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 same flaws:
They sell a dream that you can turn a complex task that requires experts, into a simple task that anyone can do. In reality, you either have a simple application that doesn't do much, or an extremely complex application that still doesn't offer the performance and flexibility of just using an expert.
You end up creating a programming via drag and drop application that is more complicated to learn than actual programming. You replace general programmers with useless tableau specialists.
It took the tableau experts weeks to do what a programmer could do in days when complex requirements came up. Most requirements were complex.
Tableau Server is very, very slow and requires massive resources to run.
Tableau had to run the full, unfiltered query so that it could generate filter lists with all of the possible options. This query was often too large to run.
I tried to buy the desktop app a few months ago and just got bogged down with the sales guy. They tried to sell the server products (with very high per-user pricing) when all I needed was 1 desktop licence and the free viewer.
It was difficult to work out if they were a consultancy, a service, or selling a product. I think those things are in conflict with one another and make it difficult to understand the level of commitment and risk.
They are/were extremely popular with many sales organizations for internal dashboarding and even some media outlets used their stuff for public websites.
Sad to see this state of things for them, as the product was true good at one point. That said, I have not touched it in 3-4 years, so not sure how competitive it is now.
If I could dabble with it for $50/year I would. $1000 though? That limits their market tremendously to big companies only. It's hard enough to get an $80 tool approved.
-- Looks like they give it free for students now, which is cool: https://www.tableau.com/academic/student. But after learning it, there's no path to bring the software with them when they move to actual companies, because of the cost.
That's what the rest of the world might call a "bad omen."
On top of that, PowerBI is subsidized in order to funnel customers for SQL Server.
Even with open source tooling, it's a large and ongoing development effort to do BI right.
I'm not saying that to bash on PowerBI. I love that product and use it heavily and promote it to clients. It just serves different purposes than Tableau.
Out of the box mapping is miles better in Tableau.
Overall Tableau is more fully-featured than Power BI. Tableau aims to be a complete BI presentation layer. Power BI is positioned as the self-service and personalized consumption component as a part of a larger BI presentation layer. Microsoft would prefer that the entirety of the BI stack be made up of their technologies, but Power BI can consume other data sources, and its reports can be embedded in other apps, so it fits into other technologies as well.
We could go feature-by-feature and Tableau would win the majority of presentation sophistication bullets (more fine-grained control of display, filtering, interactions - richer collection of built-in visualizations).
The differentiator for Power BI is more on the self-service end. Personalized dashboards (dashboard and report are two distinct concepts in Power BI) can be trivially created from published reports. Customized reports can easily be extended from published reports and datasets. There's a strong collaboration framework based on Office 365 groups and with lessons learned from SharePoint. There is also a pretty seamless upgrade path. Power Pivot models can currently be promoted to SSAS, and the expectation is for the same to be possible with Power BI models (all the same backing database technology).
I hate to be so vague, but there's a lot to both products. I'd be happy to dive deeper into some specific cases if you've got questions.
Power BI as a standalone product is pretty brutally limited in terms of data volume (250MB compressed data model is the max that can be hosted in the cloud service), and is missing the extensibility and flexibility that comes from a tool like SSRS.
As a self contained product, Tableau will likely hold the lead for some time. As a platform, I think Microsoft is beyond Tableau - they cover far more of the BI spectrum (and well, especially with SSAS) than Tableau seems to ever intend to.
It all boils down to this, in my opinion: PowerBI is for dashboards and reporting mostly. Tableau can do dashboards, but it can also do "analysis". Uncovering insights in the data that go way beyond simple cross-filtering.
In my mind, they are different tools for different purposes.
Just because you can, doesn't mean everyone will rush to do it. This is a self-service platform. Putting the data in the hands of decision makers. There is hierarchy in how people use such software:
The user: He uses only the apparent features in the GUI. Like the grid and aggregation formulas in Excel. He learns how to use the software from other people showing him how to do stuff.
The Power User: He has deeper needs, but can only be bothered to use features 1 or 2 levels deep in the GUI. Like pivot tables, vlookups and index/match, logical operator formulas in Excel. He learns how to use the software from tutorials.
The Advanced User: He has a task and does not mind getting his hands dirty in order to fix it. Uses DAX and Cube formulas. Perhaps even Macros. He learns by googling his problem and reading documentation.
The Developer: Solves the problems at the programmatic level.
Tableau occupies a very specific spot. It is brilliant for the User who only consumes dashboards via clicking on them. No explanation needed and it is super polished. It is also powerful enough for the Advanced User who can perform relatively sophisticated analyses from the interface. Generally speaking, it is not a good fit for the Power User who doesn't have the need to justify using it. It is also not a terribly good choice for the developer because it is too restrictive and the programmatic features are not well thought out.
With RedShift, you offload the actual crunching to the db that can handle billions of rows, and then visualize the results.
I have limited experience with it (only POCs), but I liked it very much.
They usually figure well in Gartner rankings
Searching "tableau" in Google stills shows their website as well as a large knowledge graph on the right hand side which tells you exactly what the company is about. There's News results at the top of the page, but there's still plenty of information, including the company website, on the first page of results.
