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Index Planning and analysis SaaS metrics › Microsoft Power BI vs Tableau
SaaS metrics and analytics · September 2026 Edition

Microsoft Power BI vs Tableau

One of twelve models named Microsoft Power BI first on the direct prompt; one named Tableau. Microsoft Power BI was named by seven of the twelve models and Tableau by six and Microsoft Power BI carries 14 labels and Tableau 11, so the shares are not directly comparable.

Microsoft Power BI

accepted challenger

Named in five categories this edition.

Tableau

accepted challenger

Named in four categories this edition.

First-choice share2%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate7%18%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#6#7A position in a field of 11; printed, not drawn.
Labels1411A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Microsoft Power BI reading right to left. Rank and label count are printed, not drawn.ChartMogul was named alongside these two in nine of the twelve direct answers. ChartMogul vs Microsoft Power BI · ChartMogul vs Tableau · ProfitWell Metrics vs Microsoft Power BI

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the saas metrics and analytics page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Microsoft Power BIFirst choices, of twelve modelsTableau
Direct11
Paraphrase00
Comparative00
Budget-constrained00
Scale-constrained00
Negative001 against Microsoft Power BI · 2 against Tableau
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Across every category in the September 2026 Edition, Microsoft Power BI and Tableau were named in the same answer 102 times, of the 140 answers naming Microsoft Power BI and the 119 naming Tableau. In those answers Tableau took the first choice one time and Microsoft Power BI twenty-one.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Microsoft Power BI and Tableau stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
Microsoft Power BI Tableau first choice named as an alternative argued againstblank: not namedEach cell is one answer, Microsoft Power BI on the left and Tableau on the right.

The direct prompt

The plain question, one answer per model, grouped by where Microsoft Power BI and Tableau stood in it.

Both were the first choice

1 of 12 modelsThe answer named them together, and the judge labeled each a first choice.
Mistral SmallMicrosoft Power BI, Tableau alternatives: Baremetrics, ChartMogul, Mixpanel

Neither was the first choice, one was named

4 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniProfitWell Metrics alternatives: Amplitude, Looker, Microsoft Power BI, Mixpanel, Tableau
Perplexity SonarFairview alternatives: Databox, Microsoft Power BI
DeepSeek V4 FlashChartMogul alternatives: Baremetrics, Looker, Microsoft Power BI, ProfitWell / Paddle Retain, Sigma Computing
MiniMax M2.5Baremetrics, ChartMogul alternatives: Microsoft Power BI

Neither was named

7 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5ChartMogul alternatives: Amplitude, Baremetrics, HubSpot Operations Hub, Looker
Gemini 3.5 FlashSubscript alternatives: ChartMogul, Equals, Maxio
Grok 4.1 FastChartMogul alternatives: Baremetrics, Looker Studio, Maxio, Paddle Retain, Stripe Sigma, Tableau/Power BI
Llama 4 Maverickno first choice
Qwen 3.7 FlashChartMogul alternatives: Catalyst, Paddle
Kimi K2ChartMogul alternatives: Baremetrics, Databox, Looker Studio
GLM 4.7 FlashXChartMogul, Databox alternatives: HockeyStack, Maxio

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Level: the same share of first choices.
Microsoft Power BI0%#– of 10
Tableau0%#– of 10
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Microsoft Power BI2%#6 of 11
Tableau2%#7 of 11
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Microsoft Power BI2%#5 of 10
Tableau2%#7 of 10
The full enterprise standing →

What the models said about Microsoft Power BI

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“Be cautious: General-purpose BI tools (Power BI, Tableau, Looker) for SaaS metrics” DeepSeek V4 Flash · negative prompt · soft negative
“the best SaaS metrics dashboard is often a custom-built solution using Power BI or Tableau on top of a modern data warehouse” Mistral Small · direct prompt · first choice

What the models said about Tableau

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“Avoid trying to build subscription metrics in generic Business Intelligence (BI) dashboards like Looker Studio, Tableau, or Databox” Gemini 3.5 Flash · negative prompt · hard negative
“custom-built solution using Power BI or Tableau on top of a modern data warehouse” Mistral Small · direct prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.