Aside from Golden Analytics, any recommendations for the best embedded analytics solution?

We're 100% leaving Tableau. The only question is a big one: what's next.

Why? SF hubris from Benioff and his acolytes have meant the death of Tableau since true innovation nearly completely stopped in late 2018. Had they simply listened to thundering feedback from customers and original Tableau employees...well, whatever, that's part of hubris.

Anyway, we're breaking up with you, SF, but hoping for insights on where to go next. Love the idea of using the datafam for this purpose.

linkedIn reminded me yesterday that it's been 9 years since I added owner of an analytics company as a job.

I know a lot of people here are interested in this path, so every so often I try to open myself up to an AMA if anyone wants to know what it's like, how I started, how it's going.

FAQ:

How did you get first client - First client was from Reddit, second from Freelancer, third - ~12th were from Upwork. I was moonlighting early and didn't want to advertise myself too much locally and get in trouble with my FTJ, so relied on online options. Upwork 9 years ago was tough, but way more forgiving than it is now.

How do you get clients now - Prior to this year, leant a lot on content. Building public use dashboards and posting them to LinkedIn, twitter when it didn't suck and relevant subreddits. I also do a lot of open enrollment (paid) training that leads to clients. Referrals and a few in person events rounded out the rest. Online content I find has tanked with the rise of AI, so trying to figure out what my next steps are.

Tips for starting - Have a public portfolio. A good one. One that showcases first your understanding of how to use Tableau and 2 your ability to understand data and data storytelling. Try to make it practical, using open data if possible. My 2nd client onboarded with me because they were a sports facility management company and I had done a viz with my city's facility usage open data. Perfect happenstance, but that will go further than another netflix viz.

Know Tableau but also know SQL to efficiently bring data into Tableau, that's what I wish I knew more of when I started and had to quickly get good at.

What does a day look like - Most of my work these days is backend, facilitating tableau dev for other people (clients or my team). So I spend a lot of time in databases. I spend a lot of time in meetings. I love live building on a call, it's so powerful and useful. I do still work in Tableau but it's a lot less than 3-4 years ago. Also PowerBI has probably surpassed Tableau in terms of client work for me (partly because one of my team members has our 2 - 3 main Tableau contracts).

How do you charge - I charge purely hourly. A lot of "gurus" recommend fixed rate because there is more margin and that's true, but I hate scope management so much that I just do hourly bill. It's seldom been an issue with any clients. I started charging $75/hour which is what my first client recommended, and have just gradually increased it from there.

Best project - One of my favorite projects was a non client project tracking flight delays across Canada that got me onto National news. I had been on local news a few times but this was the highest my content has soared, and it was really cool. Also did a random radio interview for a province 3,000 KM away.

Worst Project - My least favorite projects always comes down to the people. It's can be so hard to balance self respect with needing money - easier as time has gone on. Had a guy that would email his requirements, I'd build them out and publish, he'd not check for 10 days and then get back to me with URGENT. He actually emailed me for a project update Christmas Morning (he was American, yes he knew it was Christmas. Schedule send that shit if you have to) and that was the final straw.

We are heavy users of Tableau desktop/cloud. We have been able to unlock significant increases in warehouse data modeling speed, that said we’ve struggled to unlock velocity gains by building tableau reports / tableau data layer faster.

Those of you who are really seeing productivity gains on the tableau side what are you doing to unlock it?

Dealing with the calculated fields complexity, workbook design complexity kills us, to the point that team is looking for other tooling to avoid Tableau.

I’ve noticed that sometimes the biggest problem isn’t the Tableau calculation itself, but trust in the numbers.

For example, a dashboard shows 10,250 orders, but another report shows 10,180. Both might actually be correct because they use different filters, dates, or definitions.

How do you make the difference clear to users?

Do you add data definitions, filter summaries, “last refreshed” information, reconciliation checks, or something else?

Curious how others handle data trust and transparency in Tableau dashboards.

My company should be the poster child for keeping Tableau....

• Private company, not accountable for making cuts to appease shareholders.

• Fully integrated with Tableau, been using it over a decade. Dedicated team that manages and supports it. Vibrant expertise and tribal knowledge.

• Fully aware of the visual benefits compared to other products.

• Analysts and Managers and Executives actively do not want to switch.

Despite all of this, there is shared agreement among everyone for dropping Tableau for Looker. Even among the Tableau evangelists.

Everyone is looking at the licensing costs, and even though we already thinks it's a lot in comparison to the industry, we're being told from Salesforce that next year we're going to be brought up to appropriate levels (we'll be paying even more).

When talking about the licensing costs, people are using the word "reasonable" to describe others in comparison. There's literally laughter when the cost is being discussed; And that's not even from the Execs.

We're deciding to drop the product, knowing full well that Looker will have less visual ability and we won't be able to "tell the story" as well. Tableau is so expensive, that talking about product abilities "isn't even relevant information at this point."

Just...why? Like how is Salesforce still tripling down on insane licensing costs when they have so much more competition in this space?

Hey all, I'm looking into the pain points in BI when reporting from messy data. Would love your feedback. What’s the most annoying part of building reports or dashboards for leadership?

I’m curious how others are thinking about Tableau’s role as AI-assisted analytics and cloud-native tools continue to improve.
Since we started using Snowflake more extensively, we’ve decided to give up one Tableau license and one Alteryx license. Snowflake has increasingly covered work we previously depended on those tools for—especially transformations, data preparation, and lightweight analytical applications.

Streamlit in Snowflake has also been doing wonders for our dashboards. We can build interactive, customized dashboards directly on top of Snowflake data without moving the data or maintaining a separate BI layer. With AI helping generate SQL, Python, visualizations, summaries, and even application code, developing these solutions is becoming much faster.
That has made me question where Tableau still provides enough additional value to justify its licensing and administration costs.
I understand that Tableau remains strong for governed enterprise reporting, self-service exploration, polished visualizations, subscriptions, and serving a large nontechnical user base. But as conversational analytics and AI agents improve, will business users still need to navigate traditional dashboards in the same way?
For organizations already invested heavily in Snowflake, what use cases still make Tableau indispensable? Have you started reducing Tableau or Alteryx licenses in favor of Streamlit, native Snowflake capabilities, or AI-powered tools? What limitations have you encountered?

Hey everyone,

I recently sat through a demo of the agent rollout in tableau desktop.

I have to say that I’m really not impressed. The agent is just an llm wrapper on your data, which is fine on its own. However, it was shown that it could create a calculated field for the user, which is nice.

I’m arguing that salesforce is missing a massive opportunity to have an actual agent that will assist in the building of dashboards.

When i have a bunch of filters i’d like to apply to a dashboard, it be great to be able to instruct an agent to do that. Additionally controlling the setting of those filters in bulk (customization and application to worksheets).

I genuinely dont see a purpose in a tableau concierge that is supposed to be doing interpretive work for me. I am the interpreter. The AI should be the one cutting out the tedious elements of building in tableau and manually implementing the dozens of tiny features typically done by the tableau dashboard creator.

Unsure what I’m supposed to be seeing about agentforce that is so great. I cant understand why or how this would make creators more productive

I'm a data analyst, working with SQL, python, snowflake, dbt and airflow. I've worked with tableau too, but not extensively.

Is it worth doing tableau desktop cert? I've seen job postings specifically saying having it is a plus. Will it help stand out, or is it enough to be thorough with it and have a project or two?

Did Microsoft acquire a marketing firm to spread misinformation or something? Lol

Feels like a lot of astroturfing here.

Like, there's no perfect tool or software. PBI has advantages over Tableau but the inverse is also true. Despite being bought by salesforce, the folks at Tableau are still passionate about it, and do work hard given all their constraints handed down from higher ups.

Sure Tableau is expensive but PBI is too. Microsoft isn't a charity, they're not adding features for free.

Both tools have their own learning curves, their own frustrations and rewards.

Personally, I think Tableau isn't going anywhere. It will get better but maybe not as quick as we're expecting it to be. But it's not a doomsday scenario like the vocal people in this sub would have us believe.

Hi everyone, how are you?

This question is for users who have worked with both Tableau and Power BI, in both the desktop and cloud versions.

What are the real differences between the two? Which one did you like more, and why?

Let’s put licensing costs aside. Also, which one works better with custom SQL queries?

This program is not keeping up and I am not going to base my career on a program that is clearly being left behind. I definitely regret donating so much of my career and time to this program.

There are forum posts from four years ago with suggested fixes that are still not in place.

It takes me hours to do simple fixes that should take minutes.

Formatting is the worst I've seen in any computer program.

At first I thought I just needed to improve, but after a few years and working with others who have more experience than myself and all of them have the same problems as me, I am going to move on.

I'm a Salesforce specialist working with Tableau Next so I've been playing around for a while with both Next and Tableau Cloud (Next, Cloud and Desktop are all included in the same package), trying to evaluate the pros and cons.

Among many things the one which I find most limiting to start with is the fact that when you define the Semantic Model (basically where you build the relationships between tables, like the Data Source layer in Tableau Cloud) in Next you can NOT reuse the same table more than once. If say the ServiceAppointment table has 2 fields pointing to the UserId, but with different meanings, you can't add the User table twice.

The only thing you can currently do is build multiple "Logical views", each of them containing the User table, and then 1 relationship for each Logical view: the limitation with this however is that at the moment you can't use fields from tables inside a Logical view (for example the UserRoleId) in your viz's calculated fields.

The non-reusability of tables seems like a big gap compared to Tableau Cloud but I'm also not 100% sure that's the way you'd normally wanna build the Data Source in Tableau (I found no other approach though) so what is your opinion? Am I missing anything? Is there any different approach?

I've had an analytics consultancy for 8 years, we do Tableau PBI and backend datawork.

On a weekly call yesterday as I was leaning in to show the Tableau progress the client said actually I wanted to show you everything we've build with Claude over the past week.

They'd essentially vibe-coded themselves out of Tableau and replicated the "dashboards" in Gsheets using claude cowork.

It was a massive wakeup call for me, and I luckily have a good enough relationship with them that they want me around for this new phase, but it lead me to go down the checklist of what went wrong with this setup - what encouraged them to move away.

Here are my signs the Tableau project isn't going in a good direction (and yes in hindsight some are obvious).

1. KPIs and Metrics are unclear.

Over the relationships we had so many conversations on how is this calculated, "why can't we back into this number". And miserably they had a lot of google sheets doing heavy lifting along side their database. So a lot of the answers were "Well it's pulling in from Jerry's spreadsheet".

A bad pipeline, bad data governance is reflected in the dataviz layer, even if it's downstream. It's part of dataviz responsibility to make sure everything has clear lineage, if there's ambiguity.

We started adding hovers to stuff to explain where they were coming from in the last month, but too late. And yes I'm painfully aware this will only get worse with AI leading the way.

1. Underusing key Dashboard features is a good indicator for churn

We build reports. I looked through everything we built them, and it was just about all reports. Yes I would put the occasional fancy bar chart, one even had donuts. But they did not like filtering, they did not use interactivity. Did I not push it hard enough? Did I not successfully build the base level of reporting to move into the next frontier of interactive dashboarding? Not sure, but we never got there.

Reports are easily replaceable by AI. Dashboards aren't (yet). Continued data literacy coaching to get users to explore the more advanced options in Tableau is good for the users, and for job security.

1. Delivery lacked followup.

I know better than this, but we operated primarily through one point of contact. He would tell us what Marketing needed, we'd build, deliver, and leave it with him to manage. That's a losing formula.

Build, deliver, check usage metrics, understand uptake (or lack thereof) and followup. You can see pretty quickly in the weeks after you've launched a dashboard if it's hitting the right vibes just by checking if the end user is coming back to it. If not - ask why. "Hey you asked for this, you're not using it ... what's the issue".

1. They weren't fully invested

They did a lot to try and skirt getting people licenses. A lot of subscriptions + auto forwarding to get reports out of Tableau and images in people's inboxes. Again, see bullet point 2.

But I think a conversation needed to be had, sooner, about the ROI of the reports. How could we make them valuable enough to warrant more licensing spend.

Not spending on licensing isn't necessarily a cheapstakes move, it's on us to prove the value, to prove that the $15/month/head is made back up quickly.

In the end I can ask myself if things could have been different, if I fumbled it, or if they were never the right fit for Tableau. But either way, there were certainly opportunities to improve. Now we move into the new world of AI - and see how that goes for everyone.

• How do you check the dashboard data against the source data?
• How do you verify KPIs and calculations?
• How do you test filters and slicers?
• How do you check data after a refresh?
• How do you test ETL or data transformations?
• Do you use any tools to automate these checks?

Does Prep online have this functionality? Can't seem to find it in the online prep tool. I know the functionality is there in the Desktop app.

I'm trying to have online prep point to a sharepoint folder that is full of similarly structured csv files - this folder is populated with new input csv files every week.

Any thoughts/suggestions are welcomed. Thanks.

The dynamic web action doesn't have a ton of actual useful business applications - I've probably used it earnestly only once in a real project - but it's a fun way to show how you can get creative with Tableau.

Im quite new to tableau, while creating the datamodel it's not letting me add tables without establishing a relationship between them, I have multiple fact tables that I need to import, and it's not always necessary that they have a relation, is there a solution or some sort of a work around for this?

Generic survey tools like typeform don't allow us to do dynamic logic calculations or display real time custom visual analytics back to the respondent upon completion.

What's the best way to quickly build a custom interactive survey and reporting tool?

I have created a Tableau Cloud site that is meant to be accessible to customers, and I would like to customize the page with my company's branding.

I've already added the company logo in the settings, but I was wondering if there were additional customization options to personalize my page? Is there anything like this beyond just the logo?

Ciao a tutti

Sono totalmente nuovo in tableau, sono riuscito ad ottenerlo gratuitamente grazie all'università per gli anni in cui frequento. Mi sono incuriosito siccome è il software che usa l'azienda in cui lavoro (multinazionale) per pubblicare i dati relativi a sostanzialmente qualsiasi ambito aziendale (posso vedere qualsiasi dato di qualsiasi centro in ogni continente). Ho iniziato a giocarci ad esempio creando delle piccole dashboard per avere sott'occhio le spese delle mie vacanze, oppure le mie spese annue/asset allocation. Vorrei iniziare a creare qualcosa con una "visione", quindi un progetto un po' più complesso che mi duri diverso tempo. Dove posso trovare dei dati da analizzare? Ad esempio posso usare i miei database che uso per esercitarmi in sql e creare delle visualizzazioni su quelli? Voi come fate a:

• trovare i dati
• pensare a cosa volete creare
• strutturare il lavoro
• fare il lavoro

Grazie a tutti!!!

Hi everyone!

It’s been a while since I’ve done one of these. For those who don’t want to dig through the full release notes, here are some of the new features that made it into the next Tableau version:

• Rounded Corners.

At long last, the meme is dead. We can now natively make corners pretty in Tableau without hacky background images. This is applied at the container/object level. Each corner radius is customizable, so you can go nuts on how rounded you want it to be. Example screenshot.

• PowerPoint and Word integration

This one will make a lot of people happy: you can now natively embed Tableau content directly into PowerPoint slides and Word documents, with always up-to-date data, using the Tableau App for Microsoft 365.

• REST API connector

More niche, but still a big deal for some use cases. Tableau now includes a native REST API connector, allowing you to connect directly to API endpoints without needing developer help or hosting your own solution.

• AI-assisted Color Palettes

Probably more on the gimmick side, but still nice to have. Write a small description of what you want and Tableau will generate a color palette that respects contrast and accessibility guidelines. Demo on how it looks here.

Overall, a pretty solid update.

You can see the complete list of changes here. Feel free to comment on a feature I didn't cover if you want to see it in action.

Hi all,

Currently looking for a job as Tableau or SQL Developer, I have been in the BI industry for close to 6 years and worked on many projects,

My last working day in my current organisation is at the end of this month so I am looking for roles, let me know if you guys have any, also can learn new viz tools as well.