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About microsoft.com (Tech Companies)
This page provides details about microsoft.com (Tech Companies) which was ranked #5 out of 128 in the list of sources (7 citations (5.2% share)) in answers from AI models (OpenAI ChatGPT Latest) when they were asked the following 1 question: "What does the Analytics & BI industry look like right now? Identify the dominant market leaders and brands, best products and services, key companies and providers, influential figures and thought leaders, emerging startups and trends, major conferences and events, active professional communities, and the top publications and media that cover this industry." on Dec 30, 2025 by AI Chat Watch. This source is referenced for brands: Microsoft Power BI, Tableau, Qlik, Google Looker, ThoughtSpot +5 more.
Used by AI Models
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Pages from microsoft.com (2 links)
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| /en-us/microsoft-fabric | 5 | 1 |
| /en-us/microsoft-copilot | 2 | 10 |
Brands Referenced By This Website (10 brands)
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100% | 33 |
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81.5% | 39 |
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59.9% | 27 |
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1.6% | 25 |
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Citations from AI Responses
OpenAI ChatGPT Latest
(7 citations)
What does the Analytics & BI industry look like right now? Identify the dominant market leaders and brands, best products and services, key companies and providers, influential figures and thought leaders, emerging startups and trends, major conferences and events, active professional communities, and the top publications and media that cover this industry.
[...] f‑breed stack. The center of gravity is: **cloud data platforms + semantic/metrics layers + governed self‑service BI + AI-assisted analysis**. Key macro-shifts you’ll see across most enterprises: - **Cloud suites becoming default**: BI is increasingly bought as part of larger cloud ecosystems like [Microsoft Fabric](https://www.microsoft.com/en-us/microsoft-fabric), [Google Cloud](https://cloud.google.com/), [AWS](https://aws.amazon.com/), and [Oracle Cloud](https://www.oracle.com/cloud/). - **Lakehouse + open table formats** gaining mindshare: platforms built around the “lakehouse” idea (see [Data lakehouse (Wikipedia)](https://en.wikipedia.org/wiki/Data_la [...]
[...] Research](https://www.forrester.com/). --- ## 2) Dominant market leaders & brands (by segment) ### A) Analytics & BI “front end” platforms (dashboards, exploration, self-service) Commonly short-listed in large organizations: - [Microsoft Power BI](https://powerbi.microsoft.com/) (and the broader [Microsoft Fabric](https://www.microsoft.com/en-us/microsoft-fabric) environment) - [Tableau](https://www.tableau.com/) (Salesforce: [Salesforce](https://www.salesforce.com/)) - [Qlik](https://www.qlik.com/) - [Google Looker](https://cloud.google.com/looker) - [SAP Analytics Cloud](https://www.sap.com/products/technology-platform/analytics-cloud.html) - [IBM Cognos [...]
[...] stacks: - [Snowflake](https://www.snowflake.com/) - [Databricks](https://www.databricks.com/) - [Google BigQuery](https://cloud.google.com/bigquery) - [Amazon Redshift](https://aws.amazon.com/redshift/) - [Azure Synapse Analytics](https://azure.microsoft.com/en-us/products/synapse-analytics/) (and [Microsoft Fabric](https://www.microsoft.com/en-us/microsoft-fabric)) - [Teradata](https://www.teradata.com/) Analytic databases often used for real-time / cost-efficient workloads: - [ClickHouse](https://clickhouse.com/) - [DuckDB](https://duckdb.org/) - [SingleStore](https://www.singlestore.com/) ### C) The “must-have” adjacent layer: transformation, orchestrat [...]
[...] 3) “Best” products/services (how buyers typically define “best” today) “Best” usually depends on the dominant constraint—governance, cost, speed, skill set, or embedding. In practice, buyers tend to choose: - **Best for Microsoft-centric enterprises**: [Power BI](https://powerbi.microsoft.com/) + [Microsoft Fabric](https://www.microsoft.com/en-us/microsoft-fabric) - **Best for enterprise visualization breadth & ecosystem**: [Tableau](https://www.tableau.com/) - **Best for governed modeling + semantic consistency in Google ecosystems**: [Looker](https://cloud.google.com/looker) - **Best spreadsheet-like cloud analysis on warehouses**: [Sigma Computing](https [...]
[...] ntext, I can tailor this map 1) Are you looking at this as a **buyer**, **job seeker**, **investor**, or **builder**? 2) What’s your “home base” platform today (e.g., [Snowflake](https://www.snowflake.com/), [Databricks](https://www.databricks.com/), [BigQuery](https://cloud.google.com/bigquery), [Microsoft Fabric](https://www.microsoft.com/en-us/microsoft-fabric))? 3) Primary use case: finance BI, product analytics, operational analytics, embedded analytics, or real-time? [...]
[...] s**: reducing metric inconsistency and “dashboard drift” via centralized definitions (see [Semantic layer (Wikipedia)](https://en.wikipedia.org/wiki/Semantic_layer)). - **AI copilots embedded into BI**: natural language query, insight explanations, and assisted authoring are now table stakes (e.g., [Microsoft Copilot](https://www.microsoft.com/en-us/microsoft-copilot), [Tableau](https://www.tableau.com/), [Looker](https://cloud.google.com/looker)). - **Governance + privacy pressure**: more emphasis on catalogs, lineage, access controls, and policy-based sharing (see [Data governance (Wikipedia)](https://en.wikipedia.org/wiki/Data_governance)). For “who leads,” [...]
[...] actitioners with large communities: - [Tristan Handy](https://www.tristanhandy.com/) (founder/CEO of [dbt Labs](https://www.getdbt.com/company/)) --- ## 6) Emerging startups & notable trends to watch ### Trends - **AI-assisted BI workflows** (NLQ, automated viz building, narrative explanations): [Microsoft Copilot](https://www.microsoft.com/en-us/microsoft-copilot), [Tableau](https://www.tableau.com/), [Looker](https://cloud.google.com/looker) - **Composable analytics stacks** (swap components around the warehouse/lakehouse): [dbt](https://www.getdbt.com/), [Airbyte](https://airbyte.com/), [Apache Airflow](https://airflow.apache.org/) - **Semantic/metrics co [...]