Real ChatGPT answer · index seedeD0HypvCtSwcompleteB2B software · data and analytics platformscommercial
We are struggling with Looker dashboard performance after expanding our dataset. What BI platforms handle massive scale better?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
We are struggling with Looker dashboard performance after expanding our dataset. What BI platforms handle massive scale better?
6 real searches · 1 real-search pass
enterprise BI platforms massive data scale performance architecture Snowflake Tableau Power BI Sigma ThoughtSpot Domo 2025 2026Google ↗
OBSERVEDOther / navigational
Looker performance optimization large datasets semantic layer BigQuery query performance alternatives BIGoogle ↗
OBSERVEDComparison
Microsoft Power BI DirectLake large semantic models performance concurrency official documentationGoogle ↗
OBSERVEDComparison
Tableau Hyper extract engine performance large datasets official documentationGoogle ↗
OBSERVEDOther / navigational
Sigma computing warehouse native architecture performance concurrency officialGoogle ↗
OBSERVEDComparison
ThoughtSpot search analytics cloud scale architecture performance officialGoogle ↗
OBSERVEDOther / navigational
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (6)
Classes come from the query-classifier (a local Laya model). 6 of 6 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT6 real searches · gpt-6
enterprise BI platforms massive data scale performance architecture Snowflake Tableau Power BI Sigma ThoughtSpot Domo 2025 2026 Google ↗
Looker performance optimization large datasets semantic layer BigQuery query performance alternatives BI Google ↗
Microsoft Power BI DirectLake large semantic models performance concurrency official documentation Google ↗
Tableau Hyper extract engine performance large datasets official documentation Google ↗
Sigma computing warehouse native architecture performance concurrency official Google ↗
ThoughtSpot search analytics cloud scale architecture performance official Google ↗
- Direct Lake overview - Microsoft Fabric · learn.microsoft.com
- learn/learn-pr/wwl/design-semantic-models-scale/includes/5-configure-settings.md at main · MicrosoftDocs/learn · github.com
- Tableau Server Data Engine · help.tableau.com
- Extract Your Data · help.tableau.com
- Architecture · sigmacomputing.com
- Optimize Looker performance | Google Cloud Documentation · docs.cloud.google.com
- Optimizing Performance of LookML Queries · skills.google
- Introduction to BI Engine | BigQuery | Google Cloud Documentation · docs.cloud.google.com
- Analyze data with BI Engine and Looker | BigQuery | Google Cloud Documentation · docs.cloud.google.com
Semantic map
Every query placed by meaning (EmbeddingGemma 2, 256-d). Shaded regions are topics, nearby points are near-paraphrases, and a circle's size is how often the query came back.
Colour
SimulatedReal search
Hover a query to see its counterpart · zoom with Ctrl/⌘ + scroll, a pinch, double-click or +
Queries
6 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
enterprise BI platforms massive data scale performance architecture Snowflake Tableau Power BI Sigma ThoughtSpot Domo 2025 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Looker performance optimization large datasets semantic layer BigQuery query performance alternatives BI OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 | |
Microsoft Power BI DirectLake large semantic models performance concurrency official documentation OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 | |
Tableau Hyper extract engine performance large datasets official documentation OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Sigma computing warehouse native architecture performance concurrency official OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 | |
ThoughtSpot search analytics cloud scale architecture performance official OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |