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GoogleAI Data Analysis

Looker

Google Cloud's BI platform. Data teams define metrics, joins, and access in LookML. People explore, build dashboards, and ask natural-language questions through Gemini in Looker's Conversational Analytics. Sold as Looker (Google Cloud core) platform editions plus user licenses, separate from free Data Studio, formerly Looker Studio.

The 30-Second Take

Pick Looker if every dashboard, spreadsheet pull and AI answer must come from one set of metric definitions.

Data teams define metrics, joins and access rules once in LookML, and everyone else explores and asks questions on top of them. Gemini in Looker's Conversational Analytics composes its queries from that same model.

Best fit
Companies with a modeled warehouse that want dashboards, self-serve, and AI answers on one set of metric definitions.
Main constraint
Answer quality and self-serve depend on LookML that only trained developers maintain.
First move
Build a data agent on one or two curated Explores with verified queries. Have people who know the data test its answers.

Why

Watch the modeling load: only trained developers maintain LookML, and if it falls behind, answers degrade while the license and data token budget still grow. The cost is that modeling work plus an annual license.

Practitioner sentiment, leaders and teams−8 Mixed

26 practitioners, 80 sources reviewed, Updated Oct 26, 2026How this is measured

Read the GILD Review
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Operating stack
AI Knowledge Work

Comparisons

How does Looker compare with the alternatives?

See all 4 comparisons

  1. Looker vs Hex

    • Self-Serve Analytics

    Choose Looker for governed dashboards and AI answers on one LookML model, under an annual license. Choose Hex for SQL and Python notebooks with agents that read semantic models and endorsed data, billed per Editor seat and AI credit. Hex publishes a migration skill that rebuilds Looker dashboards as Hex apps.

  2. Looker vs Microsoft Copilot

    • Reporting & Dashboards

    The Microsoft product here is Copilot in Power BI, part of Copilot in Fabric, which runs on paid Fabric capacity (F2 or higher) or Power BI Premium (P1 or higher), metered in capacity units and licensed apart from the per-user Microsoft 365 Copilot license. Stay with the semantic model you already have: Copilot in Power BI answers from Power BI semantic models, and Gemini in Looker answers from LookML under the Looker license, with its own data token pool. Looker also connects to Power BI, so a team can keep LookML definitions and Power BI visuals together.

  3. Looker vs Databricks Genie

    • Self-Serve Analytics

    Choose Looker when your metrics live in LookML over Databricks and other databases, with dashboards and Explores on the same model. Choose Genie when a data team curates Unity Catalog data inside Databricks.

Buying and deployment

What business and product leaders should verify before rolling it out across teams.

Sourced from Google Cloud documentation

How you buy it

No list price

Annual commitments through Google sales, with 10 Standard and 2 Developer users included.

Source 1, Google, Pricing: Pricing

Details

Google's sales team sells Looker (Google Cloud core) on annual commitments of one, two, or three years. A platform edition (Standard for teams under 50 users, Enterprise, or Embed) includes 10 Standard and 2 Developer users, and further Developer, Standard, and Viewer licenses are added on top. Each edition caps API calls a month: Standard at 1,000 query and 1,000 administrative calls, Enterprise at 100,000 and 10,000, and Embed at 500,000 and 100,000. Google publishes no list prices.

Cost drivers

60M input tokens

The monthly Conversational Analytics pool on Standard. Every query also uses warehouse compute.

Source 1, Google, Pricing: PricingSource 3, Google, Conversational Analytics: Conversational Analytics

Details

The platform edition and user licenses set the license bill, and Looker sends every query it composes, Conversational Analytics answers included, to the connected database to run. Conversational Analytics has a monthly data token pool per instance, with 60M input and 1.2M output on Standard, 300M and 6M on Enterprise, and 1.2B and 24M on Embed. Unused tokens expire. Overage costs US$3.00 per million input and US$20.00 per million output tokens after the promotion ends, with at least 90 days' notice.

Where it runs

Live queries

Against your connected database. Gemini and the MCP server need a Looker-hosted instance.

Source 5, docs.cloud.google.com, Looker (Google Cloud core) locations: Looker (Google Cloud core) locationsSource 6, Google, Choosing a hosting option for Looker (original): Choosing a hosting option for Looker (original)Source 2, Google, Gemini in Looker: Gemini in LookerSource 7, Google, Looker-managed MCP server: Looker-managed MCP serverSource 3, Google, Conversational Analytics: Conversational Analytics

Details

Looker (Google Cloud core) runs in a chosen Google Cloud region. Looker (original) is Looker-hosted on Google Cloud, AWS, or Azure, or customer-hosted. Gemini in Looker and the managed MCP server require a Looker-hosted instance. Queries run live against the connected database.

What to verify

Global processing

Model calls use a global service unless EU processing applies on Looker 26.10 or later.

Source 8, Google, How Gemini in Google Cloud uses your data: How Gemini in Google Cloud uses your dataSource 3, Google, Conversational Analytics: Conversational AnalyticsSource 2, Google, Gemini in Looker: Gemini in Looker

Details

Gemini does not train on prompts or responses. Conversational Analytics keeps data at rest in the instance's region, but model processing uses a global service unless EU localized processing applies in Looker 26.10 and later. It remains outside FedRAMP High and Medium authorization boundaries. Conversations persist until users delete them, with no admin retention setting.

Signals

What is the current evidence saying about Looker?

Public accounts of Looker at work, with each finding linked to its sources.

Whose sources count

Practitioner sentiment, leaders and teams

−8 Mixed net

of 27 sources that take a side, each author counted once. Small sample.

How this figure is made

Current sentiment

Positive, mixed and negative sources

The score counts them as 7 positive, 10 mixed and 9 negative votes, one per author.

Teams praise LookML for putting everyone on the same metric definitions, and the self-serve exploration built on it. Their most frequent concerns are the LookML learning curve, which leaves model changes with a few developers, and price.

Run a pilot on questions your analysts already answer to measure how often its numbers match theirs.

Evidence field. All 80 sources, one mark each.

Arrange by

Each mark is one source: positive, mixed, negative, no opinion stated, or documentation (not counted).

By sentiment, Leaders and teams rolling it out. Every source GILD read, grouped as the field draws it.
GroupSourcesPositiveMixedNegativeNo opinion stated and not counted in the scoreDocumentation, checked and not counted
Positive770000
Mixed10010000
Negative10001000
Not counted500050
Documentation15000015
Outside this group331015800
Every source GILD read, by the quarter it was published, as the field's time axis counts it. Documentation is dated by the day it was checked.
QuarterSources
Q1 20255
Q2 202517
Q3 20256
Q4 202514
Q1 20269
Q2 20266
Q3 20264
Q4 20264
Documentation, checked15

By sentiment

15 documentation pages check facts and are not counted; 33 sit outside this group.

Hover a mark for a quick look, click it or press Enter to open its source.Tap a mark to open its source, then step to its neighbors with Previous and Next.

What practitioners praise

Top praise of 3. Each mark is a source on it; filled marks praise it.

  1. Governed Metrics9 of 11 sources on it praise it

Most common concerns

Top concern of 2. Each mark is a source on it; filled marks raise it.

  1. LookML Learning Curve10 of 11 sources on it raise it as a concern
All 80 sources behind these findings
  1. How Ramp's internal AI agents crossed a million sessionsJay Sobel, Data Platform Engineer at Ramp (Ramp's data platform team, which built the WaveDash dashboard tool and is moving off Looker onto it), Talk recap, dbt Labs blog (dbt Summit 2026), published Oct 26, 2026
  2. A Hands-On Guide to Looker Data Apps: Looker's New AI-Assisted Way of Building DashboardsMichael Murillo, Looker & BI Engineer at Astrafy (Astrafy, a Google Cloud data consultancy, building a marketing dashboard for its own marketing team with Looker Data Apps), Company blog post, Astrafy, published Oct 19, 2026
  3. Can we replace a $150k Looker with a bucket of HTML files?David Lequin, data platform engineer (self-described: Three-person data platform team at a company of about 500 people, Looker at roughly 300 seats), Personal blog post, david.lequin.dev, published Oct 14, 2026
  4. Looker pricingGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  5. LookerGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  6. Gemini in Looker overviewGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  7. Administer Gemini on your Looker (Google Cloud core) instanceGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  8. Conversational Analytics in Looker overviewGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  9. Set up Conversational Analytics in LookerGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  10. Recommended setup and rollout strategy for Conversational AnalyticsGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  11. Best practices for configuring Conversational Analytics in LookerGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  12. Create and manage Explore data agentsGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  13. Looker-managed MCP serverGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  14. Looker (Google Cloud core) features and entitlementsGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  15. Choosing a hosting option for a Looker (original) instanceGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  16. Admin settings: BI ConnectorsGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  17. Looker release notesGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  18. How Gemini products in Google Cloud use your dataGoogle (Official Looker documentation), Product documentation, checked Oct 12, 2026
  19. Post: Getting Looker data into Excel is way harder than it should beOdd_Employer_7629, Reddit poster in r/Looker (self-described: Rolling out Looker (Google Cloud core) on BigQuery to finance and controlling), Reddit post, published Oct 7, 2026
  20. The Shape and Feel of the Post-AI Data StackIan Macomber, data team lead at Ramp (Ramp's data team, which builds agent tooling for the company after years of working in Looker), Personal blog essay, Ian Macomber, published Aug 30, 2026
  21. Post: How to speed up filtering for lookml dashboards and have the looker pull data once per day instead of every time it opens?MainPressure4304, Reddit poster in r/Looker (self-described: BI analyst who converted company Tableau dashboards to LookML), Reddit post, published Aug 11, 2026
  22. Comment on: How to speed up filtering for lookml dashboards and have the looker pull data once per day instead of every time it opens?ash0550, Reddit commenter in r/Looker (self-described: Four years of Looker, team migrating away), Reddit comment, published Aug 11, 2026
  23. The scarce resource is consensus (Ian Macomber)Ian Macomber, data team lead at Ramp (Ramp's data team, after launching its Ramp Research data agent in Slack), Podcast episode show notes, The Analytics Engineering Podcast, published Jul 16, 2026
  24. Comment on: Looker-managed MCP server <> Claude Web Connector failing - anyone got this working?No-Somewhere-9675, Reddit commenter in r/Looker (self-described: Organization connecting the Looker MCP pre-GA), Reddit comment, published Jun 30, 2026
  25. Post: Looker-managed MCP server <> Claude Web Connector failing - anyone got this working?Hey-Cloud0312, Reddit poster in r/Looker (self-described: Connecting the Looker-managed MCP server to Claude at org level), Reddit post, published Jun 17, 2026
  26. Comment on: Looker vs power bi, how difficult is lookML?LateButHereAnyHow, Reddit commenter in r/Looker (self-described: Three years of Looker for health data across 67 client companies, now on Sigma), Reddit comment, published Apr 16, 2026
  27. Comment on: Looker vs power bi, how difficult is lookML?Wise_Mango_5887, Reddit commenter in r/Looker (self-described: Team moving from Power BI to Looker), Reddit comment, published Apr 14, 2026
  28. Looker feature request: support post-aggregation filtering (HAVING) for set intersection queriesmkcuadros, software engineer at Amazon Music (self-described: Team agent answering audience questions through Looker's MCP tools), GitHub issue on googleapis/mcp-toolbox, published Apr 7, 2026
  29. Comment on: Looker vs power bi, how difficult is lookML?Ifuqaround, Reddit commenter in r/Looker (self-described: Employer offers Oracle SQL and Looker), Reddit comment, published Apr 5, 2026
  30. Comment on: Looker vs power bi, how difficult is lookML?Opening_Plane2460, Reddit commenter in r/Looker (self-described: Large organization that just moved to Looker), Reddit comment, published Mar 17, 2026
  31. Splitting Looker prebuilt into looker + looker-dev breaks dev_mode isolationRoanny Lamas, data engineer at Viajes El Corte Inglés (self-described: ADK agent that writes, validates, and queries LookML through MCP Toolbox), GitHub issue on googleapis/mcp-toolbox, published Mar 3, 2026
  32. Comment on: Looker vs power bi, how difficult is lookML?IncredulousDylan, Reddit commenter in r/Looker (self-described: Built with Looker until about 2024), Reddit comment, published Feb 18, 2026
  33. Post: Looker vs power bi, how difficult is lookML?VariationSimilar3354, Reddit poster in r/Looker (self-described: Organization moving from Power BI on Fabric to Looker), Reddit post, published Feb 17, 2026
  34. Comment on: Looker vs power bi, how difficult is lookML?setemupknockem, Reddit commenter in r/Looker (self-described: Looker developer), Reddit comment, published Feb 17, 2026
  35. Comment on: Looker vs power bi, how difficult is lookML?icing9, Reddit commenter in r/Looker (self-described: More than a decade of Looker and LookML), Reddit comment, published Feb 17, 2026
  36. G2 review: Excellent LookML Governance and Seamless Embedded AnalyticsAlok K., Software Engineer at a SaaS company (G2 reviewer) (self-described: Small SaaS business (50 or fewer employees), analytics embedded for customers on PostgreSQL on AWS), G2 review, published Jan 24, 2026
  37. G2 review: Consistent Company-Wide Metrics with LookML and Easy AI-Powered Data QueriesNataporn C., IT Support (G2 reviewer) (self-described: Mid-market IT services company (51 to 1,000 employees)), G2 review, published Jan 15, 2026
  38. G2 review: Transforms Data into Actionable InsightsSteven M., Account Manager (G2 reviewer) (self-described: Enterprise marketing and advertising company (more than 1,000 employees), sales reporting), G2 review, published Jan 8, 2026
  39. G2 review: Effortless Reporting and Data ExplorationKasie L., reports builder at an internet company (G2 reviewer) (self-described: Enterprise internet company (more than 1,000 employees), order reports and dashboards for other teams), G2 review, published Dec 20, 2025
  40. G2 review: Seamless BigQuery Integration Supercharges Finance DashboardsAnonymous reviewer on G2, finance product manager at an enterprise company (self-described: Enterprise company (more than 1,000 employees), merchant and supplier unit economics on BigQuery), G2 review, published Dec 19, 2025
  41. Comment on: Looker is quietly becoming the "must-learn" BI skill for 2026Atrampoline, Reddit commenter in r/Looker (self-described: Looker user), Reddit comment, published Dec 9, 2025
  42. Comment on: Looker is quietly becoming the "must-learn" BI skill for 2026Pretend-Actuary5832, Reddit commenter in r/Looker (self-described: Looker developer), Reddit comment, published Dec 9, 2025
  43. Comment on: Looker is quietly becoming the "must-learn" BI skill for 2026elmaeg, Reddit commenter in r/Looker (self-described: Looker dashboard builder), Reddit comment, published Dec 9, 2025
  44. Claude Meets Looker: Building Smarter, Connected Analytics with Google's MCP ToolboxMark Rittman, CEO at Rittman Analytics (Rittman Analytics connecting Claude to its own Looker semantic layer through Google's MCP Toolbox), Company blog post, Rittman Analytics, published Dec 8, 2025
  45. Comment on: If you would need to choose a BI tool, would you choose Looker?Master-Arm1220, Reddit commenter in r/Looker (self-described: Company that moved from Looker to Domo), Reddit comment, published Nov 30, 2025
  46. Comment on: If you would need to choose a BI tool, would you choose Looker?Small_Sir_1641, Reddit commenter in r/Looker (self-described: Introduced Looker at their company), Reddit comment, published Nov 22, 2025
  47. Comment on: If you would need to choose a BI tool, would you choose Looker?pietro2110, Reddit commenter in r/Looker (self-described: Has built Looker and Power BI solutions), Reddit comment, published Nov 19, 2025
  48. Comment on: If you would need to choose a BI tool, would you choose Looker?r8ings, Reddit commenter in r/Looker (self-described: Company on Google Workspace and Looker), Reddit comment, published Nov 19, 2025
  49. Comment on: If you would need to choose a BI tool, would you choose Looker?burningburnerbern, Reddit commenter in r/Looker (self-described: Own Looker development), Reddit comment, published Nov 19, 2025
  50. Comment on: If you would need to choose a BI tool, would you choose Looker?cky_stew, Reddit commenter in r/Looker (self-described: Looker (not Looker Studio) deployments), Reddit comment, published Nov 19, 2025
  51. G2 review: Putting our analytics under one roof - Looker helped us bake it, not just stir it.Anonymous reviewer on G2 at a small business (self-described: Small business (50 or fewer employees); engineers, product leads, and content staff share one model), G2 review, published Nov 15, 2025
  52. G2 review: Excellent for Data Exploration Once You Get Past the Learning CurveVishal D., QA Tester (G2 reviewer) (self-described: Small business (50 or fewer employees)), G2 review, published Nov 11, 2025
  53. G2 review: Powerful Data Visualization and Analytics PlatformSidath P., Software Engineer (G2 reviewer) (self-described: Small business (50 or fewer employees), embedded dashboards), G2 review, published Sep 24, 2025
  54. How Rittman Analytics Does Financial Analytics using Looker, Fivetran and Google BigQueryMark Rittman, CEO at Rittman Analytics (Rittman Analytics, a Google Cloud partner consultancy that runs its own finance reporting on Looker over BigQuery), Company blog post, Rittman Analytics, published Sep 7, 2025
  55. Gemini CLI hallucinates responses from Looker MCPMagnús Þór Benediktsson, GitHub user (self-described: Gemini CLI answering questions on BigQuery data through the Looker MCP server), GitHub issue on google-gemini/gemini-cli, published Aug 22, 2025
  56. Comment on: Why Semantic Layers Matter (and how to build one with DuckDB)Hacker News commenter (mritchie712), founder of Definite, a competing product, describing own Looker use (self-described: Former Looker user, founder of a data platform), Hacker News comment, published Aug 19, 2025
  57. Comment on: Why are BI tools getting worse?Like_My_Turkey_Cold, Reddit commenter in r/dataengineering, certified in Power BI and Tableau (self-described: Has used Looker, Power BI, Tableau, Metabase, and Hex), Reddit comment, published Aug 14, 2025
  58. G2 review: Makes Data Exploration & Visualization Surprisingly EasyZeeshan K., Founder, CEO, and Lead Data Scientist (G2 reviewer) (self-described: Small business (50 or fewer employees)), G2 review, published Jul 25, 2025
  59. G2 review: A full-featured BI tool with an integrated semantic layer that makes self-service easierAndy M., Business Intelligence Architect (G2 reviewer, unprompted by the vendor) (self-described: Mid-market company (51 to 1,000 employees) with one BI architect and no BI analyst), G2 review, published Jun 27, 2025
  60. G2 review: Looker Review are 4 years of UsageShahrukh Q., Senior Database Engineer (G2 reviewer) (self-described: Enterprise company (more than 1,000 employees), enterprise reporting system built in Looker over four years), G2 review, published Jun 6, 2025
  61. G2 review: Robust BI Tool with Room for FlexibilitySampath K., Security IAM Engineer II (G2 reviewer) (self-described: Enterprise company (more than 1,000 employees) on BigQuery and Snowflake), G2 review, published Jun 5, 2025
  62. Comment on: Why is Looker so bad at Left Joins?RefrigeratorSalt449, Reddit commenter in r/Looker (self-described: Two years making Looker do tabular-model work), Reddit comment, published May 28, 2025
  63. Post: Why is Looker so bad at Left Joins?weed_cutter, Reddit poster in r/Looker (self-described: LookML developer), Reddit post, published May 27, 2025
  64. Comment on: Moving to Looker from Power BIMrFengYT, Reddit commenter in r/Looker (self-described: Looker user), Reddit comment, published May 10, 2025
  65. Comment on: Moving to Looker from Power BIash0550, Reddit commenter in r/Looker (self-described: Six years of Looker after SAP BO and Tableau), Reddit comment, published May 7, 2025
  66. Comment on: Moving to Looker from Power BImash_dummy, Reddit commenter in r/Looker (self-described: Two weeks of Looker after Power BI at work), Reddit comment, published May 7, 2025
  67. Comment on: Moving to Looker from Power BIPeachy1234567, Reddit commenter in r/Looker (self-described: Six years of Looker, one month of Power BI training), Reddit comment, published May 7, 2025
  68. Comment on: Moving to Looker from Power BIEffective_Slice843, Reddit commenter in r/Looker (self-described: Four months at a company using LookML), Reddit comment, published May 7, 2025
  69. Comment on: Moving to Looker from Power BIi_Perry, Reddit commenter in r/Looker (self-described: New Looker user), Reddit comment, published May 7, 2025
  70. Comment on: Moving to Looker from Power BIponaspeier, Reddit commenter in r/Looker (self-described: Freelance Looker project after three years of Power BI), Reddit comment, published May 7, 2025
  71. G2 review: Great tool if you're comfortable with SQLBharathi G., Senior Data Analyst (G2 reviewer) (self-described: Small business (50 or fewer employees), dashboards for the team), G2 review, published May 7, 2025
  72. Comment on: DRY metrics in Looker?hipsterrobot, Reddit commenter in r/Looker (self-described: Organization extending Explores), Reddit comment, published Apr 22, 2025
  73. Post: DRY metrics in Looker?badass_panda, Reddit poster in r/Looker (self-described: Organization implementing Looker at significant scale), Reddit post, published Apr 17, 2025
  74. Comment on: DRY metrics in Looker?lk500i, Reddit commenter in r/Looker (self-described: Looker practitioner), Reddit comment, published Apr 17, 2025
  75. G2 review: Scalable BI ToolOmar A., Data Engineer (G2 reviewer) (self-described: Mid-market company (51 to 1,000 employees) on Google Cloud), G2 review, published Apr 5, 2025
  76. Comment on: Thoughts on looker?Reddit commenter in r/dataengineering (itsnotaboutthecell) (self-described: Developed on Looker in a past role), Reddit comment, published Mar 14, 2025
  77. Comment on: CubeJS - A Universal OSS Semantic Layer (Maturity?)anaselkhaloui, Hacker News commenter (self-described: Company using Looker as BI and semantic layer), Hacker News comment, published Mar 13, 2025
  78. Post: Thoughts on looker?josejo9423, Reddit poster in r/dataengineering (self-described: Own Looker use), Reddit post, published Mar 13, 2025
  79. Comment on: Users don't care about your tech stackjakevoytko, Hacker News commenter (self-described: Uses Looker daily at work), Hacker News comment, published Feb 21, 2025
  80. Comment on: SQL pipe syntax available in public preview in BigQueryanon84873628, Hacker News commenter (self-described: LookML user), Hacker News comment, published Feb 13, 2025

Feb 2025 to Oct 2026.

65 sources from practitioners, by month and sentiment.

The full readExplore all Looker Signals6 praise themes, 5 concerns, 3 points of agreement and 1 disagreement across all three groups, with all 80 sources open to inspect.

Where It Fits

Where does Looker belong in the stack?

Open Where It Fits: the Stack Field and the full map

Looker is Core across Analyze, supports Automate, and touches Assist, Find, and Create.

Business area
Company-wide
Function
Knowledge Work
Operating stack
AI Knowledge Work
Primary role
Governed BI & Conversational Analytics
Looker beside the rest of its stackThe Stack Field, every product on every layer
FootprintLooker across the AI Knowledge Work stack. Bar height is its role on each layer.

  1. Assist

    1. AI assistant: Touches

      AI assistant, touches. Looker answers questions about modeled data only. Publishing data agents to Gemini Enterprise is pre-GA. The managed MCP server lets assistants and coding agents, including Gemini CLI, Claude, and Cursor, query Looker with each user's permissions.

  2. Find

    1. Web research: Touches

      Web research, touches. Looker queries company databases through LookML. A web research tool supplies cited answers from the public web.

    2. Enterprise search: Touches

      Enterprise search, touches. Semantic Search finds saved Looker content by meaning, including business terms and analytical questions. An enterprise search tool covers other company apps and documents.

  3. Create

    1. Documents: Touches

      Documents, touches. Scheduled deliveries and Connected Sheets distribute Looker results. Dashboard summaries in deliveries are pre-GA. Teams write memos and documents elsewhere.

    2. Meeting notes: Touches

      Meeting notes, touches. Looker records no meetings. Teams bring its results to meetings through dashboards and scheduled deliveries, including alerts.

  4. Analyze

    1. Data analysis: Core

      Data analysis, core. LookML defines metrics and joins over BigQuery, Snowflake, Databricks, Redshift, and other SQL databases, with access rules in the model. Explores and dashboards query those databases live. Conversational Analytics composes Looker queries from the same model to answer plain-language questions.

  5. Automate

    1. Automation: Supports

      Automation, supports. Looker runs schedules and alerts. Its pre-GA agentic workflows monitor metric thresholds or send recurring reports. Zapier or n8n handles multi-step automation across business apps.

Market mapThe layers Looker covers, and who else owns each one.

  1. Data analysis & reporting

    CoreAnalyze

  2. Workflow automation & agents

    SupportsAutomate

  3. General AI assistant

    TouchesAssist

  4. Web research & cited answers

    TouchesFind

  5. Enterprise search & company knowledge

    TouchesFind

2 more layers on the full map. Core, Supports and Touches describe coverage. They say nothing about quality.

More on Looker

  1. GILD ReviewGILD's evaluation, with the buying facts
  2. Research2 pieces
  3. Guides4 guides
  4. Where It FitsOn the AI Knowledge Work stack
  5. Related Products5 products