Our renewal got Shanghaied by an extremely greedy and over zealous sales rep who injected himself between us and our renewals reps, and wanted to turn a sub $80k renewal into damn near $200k this year and $300k next.
Needless to say it got nowhere fast and, by the time he gave up and threw us “back” to renewals, the damage had been done.
We elected to do what they thought was unthinkable and we just walked away.
My oh my, it was very, very good day, when I got to tell them to go f themselves.
One can safely assume Salesforce has very well made internal Tableau visualizations of Salepserson performance. That sort of failure would almost certainly show up with crisp drop shadows.
It is a shame, however, that the behavior of the sales rep probably made the renewals rep's chart look bad if not worse.
> One can safely assume Salesforce has very well made internal Tableau visualizations of Salesperson performance.
I can't decide whether this statement is ironic or not. Salesforce is just another big company, with committees and meetings and crisp charts that exist only to show numbers going up, not to actually identify anything as boring as actual operational performance.
Heroku is one of those things that if someone tells me their still on it without a plan to migrate I question the executive leadership at their company.
Shade of its former self, expensive, and there are plenty of better options. Really seems like the company is in zombie mode until it's eventual slow demise.
I saw Fly.io and it doesn't even offer a managed database, not to mention the fact that they have had serious reliability issues.
Heroku is pretty battle tested and mature at this point, though the feature development has stopped, I don't doubt Salesforce is now going to use it simply as a the "cloud" offering for their other products..
I agree.. but I'm surprised how little Heroku alternatives have popped up yet.. There is new contestants, mostly focussed on more global deploys, but no "Heroku but maintained" that I know of.. yet.
Thanks for the graph, but I'm looking for others that are "as far left" as heroku - eg offer db stuff (like elements), review apps, etc. I haven't seen that yet, but will take another look at Render!
Which are the players between Northflank/Fly and DO and work with Python? For example AlwaysData allows you to SSH and inspect your stuff and has managed DBs and backups.
I am not surprised. There are a handful of competitors but I believe the ship has sailed. I am a complete AWS dunce but it's too easy for me to spin up an ECS with spot machines and run my python app on it. When Heroku hit the scene and for many years, there was no easy alternative. You had to go and provision your own machines to then setup.
I actually gave up on AWS forever when trying to use ECS. It was incredibly complex and it kept failing to deploy, but cloudeatch only contained log entries for it about 20% of the time. All I could do was click redeploy over and over — sometimes there were logs, usually not. And they charged me for every single deploy. After a day and a $100 bill later, I gave up and used DigitalOcean’s hosted docker instead. I had it up she’d rubbing in under ten minutes and no bill other than the actual usage costs.
Now I avoid AWS as much as I can. Of course my employers tend to be on AWS so sadly I can’t completely avoid it, but I do my best and would never recommend it anymore.
Strange, maybe billing was different when you used it. ECS only charges for usage, you must have been requesting a lot of resources to rack up a cost that quickly. For example Ohio spot pricing is $0.01260298/hour/cpu. Deploying costs nothing.
It is a tool like any other and it is not as simple as DO's but its also a lot cheaper and more powerful once you learn the tooling. The logging on deployment is true but I think the majority/all issues I have seen with that is when the image is not configured correctly and cannot run when testing locally.
It was a problem on my end causing it, yes, but the point was that AWS deployment logs were next to useless as they didn’t even show the majority of times. On digitalocean, I got logs every time and after four or five deploy attempts had it narrowed down enough to fix my problem and get it working. All without a bill.
I don’t remember what I was charged for, I assumed it was because it was counting the few seconds of running time at the minimum billed time each time I deployed, but I’m unsure. This was in 2020. All I know is that I had a reasonably simple setup, there was an issue where it wouldn’t successfully start up, but logging was flaky at best and I was charged for my attempts.
I’ve been using AWS for years, at various employers and my own last startups, and it’s far more complex than many of its competitors. That’s ok when you need all of its features, but if you need just one or two, then the complexity gets in the way.
I think it took me maybe a 1/2 day to grok the majority of it and get a build pipeline setup. Most of that time to be honest was getting the permissions correct between the build pipeline components. I used to feel the same but found it to be not that true once using it.
Github Action (Build Docker Image) > Push Image to AWS ECR for image storage > Kick off Deploy of ECS.
You can configure your ECS cluster using the console UI or something like Terraform. Once configured its set it and forget it.
Honestly not that much more complicated compared to Heroku.
Without a doubt Heroku is ultimately easier but I found that once I spent the time playing with ECS and using LLM tools to understand permissions in AWS it made a lot more sense. Now its quick enough and cheaper for me.
I don't think the way you are doing it is the worst way. I am biggest expert here of course. I do mine via a github action, right now it triggers on merges to main but could also be setup independently.
Condensed but I use
1) "build-push-action" - github action to send an image to ECR
2) "aws ecs update-service --cluster <name> --service <service> --force-new-deployment" for the deployment
I haven’t used Heroku in a long time but I really liked the feeling of starting up a database and a container for the app with two clicks. Which are the main alternatives in that space today?
I'm working with a company who are very happy on it currently. It still works really well for them, they're ok with the cost relative to the rest of their costs.
The Salesforce reps just couldn’t help themselves. Too much Oracle in their DNA. Ruined the customer relationship, and encouraged the move to Microsoft and their “free” alternative.
I'm in the enterprise procurement world and it's mind-boggling to me how many software companies in the past two years have forced themselves to $0 revenue from us by trying to double (or more!) their already exorbitant prices.
With certain requirements from large corporations switching from usage or license-based pricing to models such as charging per employee in the overall organization, it's hard to imagine it doesn't involve a little greed. It makes the choice even easier when clear alternatives are much more economical.
Imagine for example you're a small shop with your own budget in an org the size of Alphabet with a couple of Java servers that you purchase support to the tune of $5k/year and then they all of a sudden want to charge $1,000,000/month because there are ~200k employees within your larger organization.
It gets even more convoluted when you get into hardware support, where the support itself outside of warranty can be more expensive annually than replacing the hardware and getting N years of support with warranty.
We're a Power BI house with eight companies in a holding company. Power BI also has a high-security option, which is essential for us for security compliance requirements on our government contracts. We also have a blanket license so everyone can see the dashboards, and we're about to upgrade to Premium company-wide.
It took some time for me to switch from Excel paradigm to Power BI paradigm, but once it clicked, I've never looked back.
I was a big Tableau champion at our org. Lots of dashboards, led a user group, was the go-to expert for a while (think 10 years ago). For us, what killed it was the pricing. They got very greedy very fast. Justifying a 4-digit license, per desktop, was the real killer. We just couldn’t, so the creation of dashboards became a tool of a “priesthood” of sorts. Everyone loved the way the dashboards looked and performed, but people very, very rarely used them. After years trying, I can remember ONE decision that was sorta-adopted based on a dataviz.
PowerBI are their lunch because it was “free” with the rest of our Microsoft stuff, so everyone could make the shiny dashboards no one uses instead of just a few.
In some cases we just wrote our own d3-based visualizations. It was easier than dealing with the constant licensing headaches Tableau brought.
Haha funny hearing the other side of the story to this, i was a front end dev during the tableu peak who helped create several custom dashboards in JavaScript...for multiple different companies!
I worked on so many that eventually i came to hate making them lol, data viz can be extremely subjective and you get into weird paradigms of how much data viz you display vs user actions on that snapshot of data (ex. viewing details, exporting to diff formats, printing the dashboard with no cut-offs, manually refreshing stale data vs auto refresh)
Microsoft like any software company will raise prices on their tools similar to tableau or oracle in the past.
Microsoft uniquely has a large portion of the fortune 100-500 as customers. They have already had that market from office, m365, etc and will grow those things.
Microsoft is relatively early in the licensing lifecycle arc for cloud.
This will happen relative to the maturity of offering, uptake/demand to pricing.
Some of this can already be seen with the Business central pricing.
Again, the above is not to single Microsoft out. Only that their products are relatively young but developing extremely quickly and the execution of the pricing models will be relative to a lot of things like demand, and stock prices.
I was an early Tableau adopter and promoter in my org many years back.
At the time the incumbent, Qliksense, was lagging badly and there was genuine grass roots support for Tableau as our next gen BI tool. Adoption grew significantly and people were happy...for a while. I remember reaching out the founder/CEO at the time and getting responses back. It was great.
Fast forward today and its different, over time Tableau dissatisfaction grew, I think a lot of it was the fact that our use-cases got more advanced and performance dropped and not being able to understand the complex SQL it was generating didn't help. Also Qliksense got noticeably better UX and importantly was cheaper. Today, MS PowerBI which came from left field, is really the front runner for us.
Parking this situation for a second I think the real issue is that people are getting a bit overwhelmed with dashboards. I have access to near 100 across the three platforms, they more or less do the same thing and are thus somewhat commoditized, I don't feel passionate about any of them as I did back in the day with Tableau. Worse, I have to spend mental bandwidth figuring out which one I need to open to answer my query, then I have to spend time navigating the UX to get my answer so I can move on with the task in hand.
We don't necessary need more dashboards, just faster ways to go from question to reliable answer where information can be pushed rather than pulled, especially if data points start looking anomalous over time.
Note - If your a startup in this field looking to upend the BI space reach out, I have spent a lot of time in this space over the years.
Speaking of too many dashboards, my opinion at this point is that Tableau is where data goes to die. I have so many dashboards that are created in my organization but each dashboard gets one or less views per month. No one ever looks at these dashboards that get created.
My feeling is that these dashboards were probably more like one-time reports that someone decided to automate. But there's definitely a sense of Tableau fatigue. And I don't know if switching to a different technology like Power BI will make that any better.
Do most data-driven decisions need to be made daily?
Sometimes you just need to see the data once or month or once a quarter to make a decision. Sometimes, you just need to see the data once! (an ad hoc analysis in Excel)
We should think of the rate at which we need to act on decisions, and it need not always be a frenetic "now, now, now"
Dashboards have a very long tail depending on use case.
You've got daily driver exec and performance dashboards, then you have over time trend dashboards, and finally you have drill down self serve explore of data export tools. Alerting should be separate.
It's expected that most dashboards will not be checked often, trends don't change daily so it's usually not meaningful to look at most metrics daily. Self serve tools are only needed occasionally, but exist as a cost savings on data teams doing low effort high time tasks.
Dashboard tools and spreadsheets are the only good tools for sharing data, I find most reports and spreadsheets are actually just one offs.
I go back to thinking about how the data can be pushed rather than pulled. Whilst BI tools have some solutions I never found anything great so ended up with homebrew scripts. Definitely an opportunity space.
Denial: "Tableau will become a tool in the Salesforce toolbox that major players will continue to use."
Anger: "Salesforce executives mentioning Tableau less than Slack or Mulesoft on their public calls ... Meanwhile, Microsoft's Power BI is on a hot streak."
Bargaining: "I believe it'll be a consistent player at large institutions who typically go through complex project and procurement processes."
Depression: "It will no longer be the hot new tool that will be embraced by SMBs. The community will not have the hope and excitement it had in the 2010s."
Acceptance: "The magic is no longer there and that's ok. Nothing lasts forever."
I hate Tableau with a passion. The main bugbear is that viewers can't see the SQL code the dashboards execute. I am no fan of Looker, but the "Explore here" allows other users to see the SQL and tweak it if needed. Most intermediate data stakeholders are confident enough to modify the where clause to suit their custom needs, allowing them to self-serve.
The licensing costs are prohibitive, too. It is almost unaffordable to share Tableau dashboards with your customers and, instead, have to send them static PDFs of your dashboard.
Beyond that, the Tableau infrastructure feels like something from the last century. Data is cached on the server using data extracts rather than following a more modern caching infrastructure.
No such luck in my current role, Looker and PowerBI are both in use by different bits of the org and nobody has the ability to delve into the underlying figures.
I also hate Tableau for this reason. However, it's a bad pattern to be storing custom SQL in a BI tool IMO. Better to create tables or views which hold your report logic and are stored in git. That way you're decoupling defining metrics and business logic from your BI tool, making that information queryable in your warehouse by users or other tools (and easily viewable!).
It's a best practice yes, but in practice when you produce any data mart you end up getting questions to power deep dives and that's where custom SQL ends up coming from. There's usually a right way to answer the question, and a fast way with custom SQL, and with ad-hocs the fast way wins every time.
Here's an example, you do a customers rollup and an orders rollup, but a user asks for average order value of return customers buying product X. In SQL, that's a semi join of order line items, on your orders table and an inner join on daily customers to determine if they're a new customer. But no BI tool I've ever used has semi joins, so when you join in the tool your order values are multiplied and you're back to custom SQL to fix it.
It's that or build a whole new mart to answer this one question.
Looker is obscenely expensive compared to Tableau. Also the UI is bad.
The caching of Tableau is a huge money safer and huge performance boost if you e.g. use it with BigQuery (cut our BG costs by 80%).
As with every data tool, you need strong data governance, or everyone will define their own metric for revenue and then you have endless discussions about "why the data is wrong" (it isn't).
The biggest benefit to me is every marketing person knows Tableau and with a self explaining table structure (e.g. DBT on top of BigQuery) is self serving.
The only good thing with Looker is their data journeys, which Tableau doesn't have.
The worst (for EU/GDPR at least) feature of Looker is how people can send emails from a query (circumventing corporate email infrastructure, blacklists, data protection etc.). Can you say "Intern sends spam mail to millions of customers because they thought this was a good idea".
Before they were acquired by Google, looker had a bunch of really engaged community support people, and the docs were great for what the product did. There were learning paths for different types of users and tutorials linked to references in a way that made sense. I learned a lot about effective documentation (and looker!) from going through what they had.
Even if 100 US-based community support folks were making $300K in total comp, why would you not spend $30MM to keep your $2.6B acquisition humming along? A bit mystifying.
I think they should keep acquisitions under Alphabet and separate from Google. What is the point of having umbrella corporation if not going to use it?
I am not recommending Looker either, but data extract stored on the server? That is a last-century solution. We often hit data limits in Tableau online as colleagues get overzealous.
Beyond that, it is also a major GDPR headache in Europe. If someone uses their personal account, with elevated access, you suddenly have a data extract on the Tableau Online server that contains personal data, with no way to enforce retention periods.
My problem with Mode is you often end up with a ton of copy and pasted SQL and no visibility or capability of changing it with updates in the underlying data. It really hurts data governance over the long run.
I like the notebooks feature, the integration of output cells with reports is so so, but it's the best balance between exploratory and reporting tool I've seen.
I found the parameterized code powerful but creating a basic report with lots of filters and a few parameters was very slow.
I don't know jack about Tableau, but if the alternative is Power BI, I got a feeling they may be safe.
My current company sells telephony and call-center analytics for MS Teams using our software, and during pre-sales meeting, one of the staple questions is "So we can avoid Power BI entirely?" followed by a minor thanksgiving ceremony and presentation of credit card. I get a feeling it's not too dear to the hearts of its users.
If you haven't used PowerBI recently, let me tell you it is better than Tableau. In my previous work, using PowerBI I can easily drag and drop dimensions and it can suggest data visualization in browser. Now I have tableau and I have to open the laggy Tableau Creator, wait for a sync, then build a visualization from scratch. Maybe its poorly implemented at the new place, but I avoid it when I can - its easier and faster to download the raw data and visualized it in Google Sheets even
This is so interesting as my experience with PowerBI is that it’s just not as good. Not just that the figures look worse and have worse default colors, but functionality-wise it’s just more of a hassle.
What’s nice is that it’s better than Excel so if you want to replace Excel, PBI is great. But if you want a functional data viz that you’re not embarrassed to put on your web site, I’m not sure PBI works.
I'm the opposite. I love Tableau Creator and hate working in the browser. There's also no Power BI creator desktop app for Mac (nor will there ever be, I guess), so I refuse to use it.
I work for $LARGE_ENTERPRISE_CONSULTING_FIRM and I'd really could do without Power bi. It's so sluggish and a time-waste. If your product is even half-good, I can see why they like it. What does it do exactly?
Power BI is great, and so is Tableau. (Or at least when I used them a few years ago.)
Most people just don’t to analyze data and hardly even know how to use Excel, so something like Power BI or Tableau looks like rocket science when really these tools should make you feel like you’re upgrading to power tools from basic hand tools.
Looker might look attractive, but it is missing so many basic features it is not competitive. You can't even query a view in BigQuery, you can't use window functions in data sources. All error messages are entirely opaque. Access management is very limited etc.
I'm going to hazard a guess based on my experience of being the one who brought it to my current employer after learning it at a previous employer: it's really hard to understand for awhile, especially coming from Excel. The paradigm required to build anything more than SUM or AVERAGE can be very unintuitive and feels almost like black magic.
It takes a lot of trial and error and patience to finally grasp how Power BI handles calculations if you are used to the freedom of Excel.
That being said, once it clicks, it feels like you are a magician, and you can do really advanced analytics on giant tables, which is great.
We pull a bunch of data out of the guts of MS Project 2010 and do a lot of custom analysis on it. It took about two years to go from scratch to a set of reports that served everyone's needs that also required minimal maintenance.
Then we got purchased by a larger company, so now the work is in rolling out a similar set of reports for the sister companies, as well as rolling them up into corporate-wide reports. It's a lot of fun.
To put things in context, our small claim to fame is anyway getting some aggregate data about lost calls and attempts that is not possible to produce in Power BI directly[1]. So it's likely that they would buy or not buy it even if it was based on Power BI itself.
There seems to be a lot of shade here at Power BI.
Forgetting Microsoft’s dominance in the market, I’ve much appreciated Microsoft’s approach to data visualization which is soft on the visuals, but gradually improving them and hard on the programming aspects, such as Power Query or “M” and Data Analysis Expressions (“DAX”). The former they have opened to anyone to create via Power BI visuals SDK.
The reason I say this is because something that would take me hours to do in Tableau maybe only take a few minutes with Power BI’s mashup language (Power Query) and the Functional Language DAX. The ability to create temporary tables on the fly and utilize variables and the hundreds of other things you can do with DAX to create complex measures, calculated columns, etc. feels empowering. Most people I’ve spoken to who’ve gone away from Tableau to Power BI and used it long enough start to really appreciate it for the vast capabilities.
Additionally, the latest Power BI visual calculations feature released has made the learning curve a lot shorter for those newer to DAX and all our lives much easier.
On the visuals side there has been a lot of entrepreneurship to create custom visuals with the SDK to do a lot of visuals that just weren’t available in Tableau. So many that I have a hard time going back to Tableau because its missing a visual I need.
Lastly, not many talk about the fact the IT loves it in that its got so many capabilities for providing data governance and security through its various features.
Update and one final thought: there is some genius to me in how Microsoft seemed to have created an abstraction that allows the platform to grow independently and greatly on so many fronts - DAX with new functions and features, the Power BI Visuals and their SDK to do more and keep in with user interface changes, and their BI model approach (which now allows GIT versioning with readability changes).
I’ve done the microstrategy, powerbi, tableau dance for about 3 years and I wasn’t impressed.
It’s easy to do easy things and hard to do hard things.
The versioning is quite bad.
The powerBI gateways are complex to maintain, expensive and incomprehensible when they don’t work (update failed? Good luck! Out of quota? Times out? Haha…)
DAX is pretty; but when it’s big, it’s spaghetti. Worse than SQL.
The custom components are frustratingly difficult to get right because they have to be extremely flexible.
…but, sure; it is what it is.
The ecosystem is pretty good.
Lots of documentation on how to do trivial things.
It’s ok.
I would avoid it if I could though; there’s a deep well of suffering to anyone who has to look after the stuff that people “whip together quickly” in PowerBI.
Wouldn’t say love but prefer over the alternatives. I still find the user interfaces could have been designed better if they were not so focused on matching like other office products. I wish it was as nice as it is to wireframe in Figma. The ribbon and other office elements are dated and not as conducive to todays standard where good collaboration tools is helpful to bringing developers and designers together while being efficient.
> The versioning is quite bad.
Agreed, but it’s got better over the years. Especially in the most recent release of Power BI projects. I feel that Microsoft’s strategy is to provide this new format and let independent developers create versioning tools while they take on higher priorities. They have often taken things those developers have created and incorporated them into their products.
As with all the product requests, you got to pick your battles - I don’t defend which ones they choose. I’m just happy to finally have GIT versioning.
> DAX is pretty; but when it’s big, it’s spaghetti. Worse than SQL.
I agree 100%. I liked how Tableau had a more SQL feeling syntax. I luckily come from an Excel heavy background so adopting was easier than some. I find that most of the verbose code is due to dealing with row and filter contexts which in DAX can be frustrating. Debugging is difficult… I can go on.
With that said, others have offering differing opinions (see: https://www.sqlbi.com/blog/alberto/2020/06/20/7-reasons-dax-...).
All I can say is that I feel there is probably could have been a better syntax / functional language then the one created to produce the same functionality and maintain independence.
my biggest issue with Power BI after building washboarding for hospitals was that they are dangerous.
There are impossible to drill down and understand - "where did this data come from" - how was this calculated.
Similar to other comments, you can version, it's beyond hard to error check. A python or sql script you can at least verify and recreate. I view Power BI as just the new excel - big files full of hidden errors.
My biggest complaint with powerbi is that there’s no versioning and collaboration across multiple authors is really hard. I can’t put it in git other than a binary blob and so that means for anything serious I have to just hope nobody goes in and breaks stuff.
At least tableau project files are just xml so you can stick it in git and have ugly merge requests. And rollback to versions if necessary.
The fact that Microsoft doesn’t even see this is a problem is infuriating and makes it hard for any serious data work where you need reproducibility and auditability.
I use tableau for scientific, engineering and operations data visualization and it’s a breath of fresh air compared to my years spent writing pages of MATLAB/matplotlib/seaborn/bokeh/plotly code just to get something presentable. For many use-cases it’s even better and faster than JMP’s graph builder, and that’s saying something. The major missing feature is stats tooling (t-tests and CI-based error bars), but the number of use cases that don’t require these is large and the time saved from Tableau’s “immediately presentable” defaults is huge.
My limited experience with Tableau is that it felt like Excel on speed. And heavily burdened by legacy (just like Excel or any Microsoft product is by the way).
While what we wanted was something that was SQL-native.
Back in the days we opted for a tool called Chartio which was later engulfed by Atlassian/Jira. Not sure what happened to it after, but it suited our purpose fine enough. Just line-charts and easily editable SQL.
I have some experience with Superset, but it was not really built for customer facing dashboards. Mainly useful for internal use.
Blazer as someone else posted sounds interesting. May check it out.
You might be interested in Evidence, a SQL-based open source BI tool where all content is version-controllable. Disclaimer: I’m one of the maintainers. A lot of companies use Evidence for customer facing and embedded reporting.
What’s different between an internal dashboard and a customer facing one? I am mostly asking what specifically is missing from Apache Superset as we are seriously looking into it… for internal use
And this would be fine if you could lock down arbitrary input in e.g. dropdowns, but it was still possible to input arbitrary strings even in a dropdown because of the choice of widget.
I've been using Tableau since 2013 to deploy dashboards, which in my case are front ends to ML model output. (for me, I used it as a Streamlit before Streamlit existed)
People think of Tableau as a dashboard tool, which it is. But it's also a great tool for doing EDA (exploratory data analysis) on multidimensional data. Instead of writing lots of seaborn/ggplot code (and having to remember the syntax), you can just move things around in Tableau in a fraction of the time.
The downside of Tableau is that you have to have a strong relational database way of thinking to use it effectively. You have to think in terms of aggregations, and occasionally in terms of window functions (Table calculations in Tableau). Tableau was (is?) a much more powerful tool than Power BI (at least this was true in 2019 when I last used PowerBI).
Tableau has never been a simple tool by any means. I was a scientist but I used to run Tableau training in my workplace, and I could see how long it took for things to click for most folks. Once you got beyond a few bar charts, things got really complex (partly because you were unlocking a lot of power through relational operations -- in data analysis, there's rarely power without complexity)
Relational thinking is a very powerful way to think about (and execute) computation on large-scale data in a performant way -- it is after all the algebra of dataframes -- but I've come to appreciate that it is beyond most people. Even software engineers struggle to think relationally -- many still think in for-loops.
Also, things that were seemingly easy to do in Excel -- like doing a row and column cell calculation -- were very difficult. You had to think about the corresponding SQL manipulation and then reproduce it in Tableau....
... but I think most people just want to plot nice graphs from their Excel data and show it to their bosses. (which they can do with Tableau, but so can they with Power BI)
Side note: I have a copy of Tableau 2023 but it seems to have reached a feature plateau -- it is barely different from the Tableau of 2020.
>I've come to appreciate that it is beyond most people
I had the same experience. Before, my company tried several times and failed to implement enterprise dashboards and reporting. I was able to champion Tableau and get it off the ground and even the board of directors peruse the dashboards. I thought I had a huge win. I could not believe the amount of negativity I since received.
That is I believe enterprise reporting is essentially a people problem. The people who looks bad because of the metrics will always blame the tool. They won't be happy until they can manipulate the tool and massage the data until the metric becomes meaningless. In other words, it is convenient to blame the reporting if their report card shows they are failing.
I’ve never used RapidMiner so I couldn’t say. So Tableau isn’t a full fledged statistical tool. It does have all the basic statistical functions but it doesn’t really focus on that. What it is is a visualization tool. You can actually see and touch the data in multiple dimensions by slicing and dicing it.
Statistical tests are good but they are summary statistics. Often you can get a lot of insight by just looking at the raw data. Tableau lets you see the actual outliers and ask yourself why they are there and drilling down to find out more.
The simple act of looking at the data as-is and asking the questions — before jumping to statistical testing — is an underrated discipline because it seems too simple and unsophisticated. But it yields insights that many statistical techniques will not.
I've never used Tableau, but heard a lot of hate about it. However, in my previous role, we were big fans of Metabase (https://metabase.com). You can also self-host it, which was a huge win for us.
I’m not sure this is totally on Salesforce as the Tableau product has gotten so sluggish and inflexible. At my last job I started dumping data from Tableau to CSV (don’t get me started on the crap CSVs that Tableau generates) and importing to R for analysis. Good riddance.
We have Tableau but I've never found it particularly useful, as most of what I do is very exploratory and Tableau seems more like a place to build final presentation of things that will just go to gather dust.
I now use both of these tools below (no affiliation), which you might find interesting.
I don't use Tableau but had similar feelings recently with Databricks. Tools like these are probably fine for folks who want more grunt than a laptop without needing to learn much about cloud, infrastructure or security. But for me, it feels like a straight jacket. It lets you get going quickly but at the expense of flexibility. Slowly but surely the warts become apparent.
A year or two really isn't a lot of time (for an individual nor company) to invest in order to build long term skills in powerful tools that side step inflexible (and expensive) platforms.
The place I work at uses Tableau, and it is thriving there. If it was up to me though, we'd move to some open source BI tool - but in the end, we're paying for Tableau for three reasons:
1) Premium (24/7) support if needed.
2) In-house tableau consultants.
3) Too many production reports have already been written in Tableau.
With that said, I've experienced some frustration with Tableau. Want writeback combability? That'll be thousands (if not tens of thousands) of *dollars per year* in additional license fees.
Want some other feature, same deal.
With that said, the licenses have grown so much in the past few years that our stakeholders have started asking around for analysts to check out competitors and OS tools.
We had exactly the same list of objections to moving from Business Objects. Then, in its infinite wisdom, our holding company signed with Salesforce and we moved to Tableau. Significant work but relational is so mature that swapping the reporting layer is a safe migration for anyone... Good thing because it is probably not the last occurence !
I'm currently doing BI evaluation for improvement of the current toolkit, so I might use this comment section for some BI experts' advice.
We mostly use Looker Studio + Metabase currently.
Investigating Tableau, Looker, PowerBI, Sisense, Omni currently. PowerBI is great, but BigQuery integration seems to be lagging. Is there a way to get such a tool without paying $50K a year? Everything so far is only a "nice to have" upgrade over our mostly free toolkit. We also care about good geospatial visualizations and embedding reports for users without requiring a login.
Snowflake purchased Streamlit. When Snowflake has all the kinks worked out, I would create Streamlit applications directly in Snowflake and be done with it.
The best part of these dashboards is when the Big Four consultant creates The Perfect Dashboard, then asks to embed that nested unresponsive iframe mess into a web app. "Why it's so tiny, fonts are unreadable, and it's packed with scrollbars?!"
When I played around with Tableau it felt much more intuitive and easy to use than PowerBI. But I guess since people already had a contract with Microsoft for whatever product, adding PowerBI there was easier than pitching an entirely new contract for this product that ticked similar feature boxes. I am sad because I would very much prefer Tableau could exist for many years as a reasonable competitor otherwise I predict Power BI will just stagnate.
A customer of ours at ToolJet, specializing in service-based offerings, traditionally used Tableau for their analytics needs. They decided to give us a shot and started moving some of their customers over to ToolJet, taking advantage of our Plotly-based chart component for visualizations. While the initial lift to replicate their Tableau setups in ToolJet is non-trivial, the value proposition is turning out to be significantly more compelling. They're now confidently migrating more customers.
They're aware that our platform might hit some snags with the more complex use cases but most of their customers have similar use cases that are less complex.
Needless to say it got nowhere fast and, by the time he gave up and threw us “back” to renewals, the damage had been done.
We elected to do what they thought was unthinkable and we just walked away.
My oh my, it was very, very good day, when I got to tell them to go f themselves.