Index › Finance › Products › Power Query · November 2026 Edition
3 categories · Named, not ranked

Power Query

–Too few to rank
5/14Models named it
0First choices
2Warnings
November 2026 Edition · all company sizes counted.
Ranked inFinancial consolidation #66 mid-marketFinancial reporting and dashboards #84Corporate tax provision #70
What AI models recommend

Named, too few times to rank.

A product needs 10 labels in a category before a share is stated. Power Query has 5.

Why models recommend it

“Looker Studio (formerly Data Studio) or Microsoft Excel/Power Query (if data volume allows) are often safer bets”Qwen 3.7 Flash · Negative question · first choice
“Power Query: More robust than Excel's built-in consolidate”GLM 4.7 FlashX · Negative question · first choice

What gives them pause

“Microsoft’s Power Query guidance explicitly says not to use the “Ignore the Privacy Levels” / Fast Combine option because it can expose sensitive data across sources.”GPT-5.4 mini · Negative question · warning
“more manual logic, weaker controls, and greater maintenance risk”Perplexity Sonar · Comparative question · warning

Also on the shortlist

The products named in the same answers as Power Query, over the 7 answers that named it, and how often each was the first choice instead.

A side-by-side page exists where both products are among a category's top eight.

How this is measured

Fourteen AI models from 12 labs are asked the same buying questions six ways, for three company sizes. Standings refresh every edition.

Gane sells AI visibility software. No company can pay to change a result.

Read the method →

Sources returned with these answers

The sites and pages the answers that named Power Query came back with. A fact about retrieval, not a cause of the answer.

Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted. These counts come from 7 of the 7 answers that named Power Query and are not a share of its labels.

By model

How each model answered on Power Query across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ModelFirst choiceAlternativeMentionWarningLabels
Claude Haiku 4.500000
GPT-5.4 mini00011
Gemini 3.5 Flash00101
Perplexity Sonar00011
Grok 4.2000000
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash10001
Kimi K200000
GLM 4.7 FlashX10001
MiniMax M2.500000
GPT-6 Luna00000
Muse Glimmer 30B00000