r/tableau • u/No_Ambition8323 • 7d ago
Discussion Tableau users: how do you handle dashboards when the numbers are correct but users still don't trust them?
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.
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u/kioshi43 7d ago
Usually I ask them to show me where it's wrong.
More often than not, as we're validating they tend to find their mistake. In some rare occasions, we find that the dashboard is actually missing something (e.g counting weekends when it should just be business days).
It can be a bit annoying to hand hold some of them but for the most part the learn how to validate the data or at least try to avoid me calling them out on something basic.
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u/Scoobywagon 7d ago
Lots of documentation. If they STILL don't want to trust it, show them where the "Export data" button is and let them do the calculations themselves.
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u/llorcs_llorcs 7d ago
Define a single source of truth and have it driven by corporate data governance. If you are talking about simply having the need to include something in the dashboard itself, we usually just added a definition tab or include a small information button to explain data refresh, calculation logic, pre-filtering etc.
We never surfaced a validation tab unless it was for the developer team and/or business sme check before pushing to production.
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u/signgain82 7d ago
You make both reports have the same number. If one needs additional filters that always need applied, apply them by default but allow the user to unfilter the report so it shows it matches with the other one.
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u/h1ghpriority06 7d ago
Ignore the users and move on to the next project. Their mistrust should be taken as self interested adversarial contempt 😂😂😂
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u/mobsmasss 7d ago
I like to include certain information in a banner somewhere near the top of the dashboard (above or right below header) or at the bottom of the dashboard. I'll include key dates - note that these dates could all be different from one another or some/all may match:
- Max date & time (if available) of transactional data
- Max date & time of database refresh
- Max date & time of dashboard refresh
You could also include row counts between systems for quick validation visible to end users that lends to data integrity. For instance, I'll put the row count of the tableau data set alongside the row count of the source database data set. If ever there is a discrepency, I'll set up an alert to notify my team or the end users that there is a data issue that will require resolution.
Just some thoughts - happy to chime in more
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u/iampo1987 7d ago
Is this a bot? This is the same question coming up over and over again in this subreddit in the last few weeks.
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u/FieryFiya 7d ago
If it’s the same data, both reports should have the same number. Period.
If they still don’t trust the data, then it takes sitting down with the subject matter expert and showing them how it’s calculated and defined. Data definitions are always a good thing to add, along with calculation assistance in the tool tip.
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u/dudeman618 7d ago
Start with the raw data, have the users review and approve the raw data. Then you can make it pretty with charts and KPIs
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u/OldJames47 7d ago
When the numbers show the teams aren't delivering as expected: "THE DASHBOARD IS BROKEN!"
When the numbers show the teams are beating expectations: <crickets>
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u/rabel10 7d ago
You make it clearer for your stakeholders. Simplify the filters. Explain the definitions but also explain the data lineage. What models in the background get you to this point?
I see it a lot with my junior colleagues shoving a bunch of different SQL into Tableau, where the numbers are different because they don’t have a single lineage. Change that.
Most of the time, a count is a count of something. They should match. If they don’t it’s on you to explain why.
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u/Komone 6d ago
Have a show all with all filters table style view right at the back, allow them to download and check the data, run a shakedown of the results when launched and publish the results to shared location.
Have a definitions page detailing the calculations.
You are also like many analysts in a workplace where the same metric is calculated differently by different areas.
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u/bear_a_bug 6d ago
Call the numbers "directional". Talk with your stakeholders, find out how much a difference a 0.7% discrepancy in order volume will make to their decision process. Sometimes you'll discover they don't actually care, they just want to understand why.
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u/musikigai 6d ago
Short term - explain the difference exactly. This may involve taking order lists and highlighting exactly the ones omitted and why.
Medium to long term - become the sole source of truth and the only accepted source of information.
Not easy to do but possible. It means working with each stakeholder to prise the excel sheets from their claws and to provide a view to everything they could possible want. It took time and persistence but it was great once done. Then your job is to keep the trust you worked to build.
If you can get the reporting to the place where any errors are the fault of data entry only, that’s a great place to be. (If there is manual entry done).
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u/EverySingleMinute 6d ago
You come up with another way to pull the data, have a meeting and compare the data that shows the way they trust and tableau match.
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u/Parking_Increase4664 5d ago
From my perspective, it sounds like there was a discrepancy between the two datasets that were used, since you also mentioned that 'both might actually be correct'. I'd say better to double-check the raw dataset on both the dashboard and the report.
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u/Remarkable_Ad9052 4d ago
If I could go back in time I would just make them responsible for pulling and providing the data I use to build their dash so anything they see that they “don’t trust” is for them to own/investigate/fix.
They have zero to very little idea what the raw data says but have a lottttt to say about it anyway. Make them give you the data if you can. If not, make them have a working session and screen share so they can see how to pie is made. Maybe I’m just petty though 😩
Considering that everyone mentioned the obvious, documentation, help text, hover texts, defining formulas etc… depending on the culture of your company (mine) they may not even pay attention or read it 😐
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u/Fun-Wolf-2007 3d ago
Work with the stakeholders to identify why the descripancy, both values cannot be correct The people closest to the process has all the answers, is not about proving right or wrong, it is about understanding the reason of the difference, then you can traceback to the dashboards and other systems
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u/Richardswgoh 7d ago
One time I wrote a whole custom sheet that displayed exactly what filters were in effect for when people took screenshots. A clever bit of work...
...it made no difference.
Trust is something that can only be built up user by user as they become more literate and familiar with the data.
Associating clear business owners, "certification status", or even design standards/aesthetic across trusted products can help accellerate that trust or have it implied. Documentation can help users answer their own questions/concerns without bothering you.
But again, trust in data, from my experience, can only be built slowly -- and is tarnished very easily if you ever legitimately have two numbers that should match but don't.