{{ domain.value }}
About en.wikipedia.org (Charity & Non-profit)
This page provides details about en.wikipedia.org (Charity & Non-profit) which was ranked #10 out of 255 in the list of sources (15 citations (2.2% share)) in answers from AI models (Anthropic Claude Sonnet (latest),
OpenAI ChatGPT Latest) when they were asked the following 3 questions: "What are the best Analytics & BI options available today? Please provide a comprehensive overview including: the leading brands and products, top companies and service providers, recognized experts and thought leaders, promising startups and new market entrants, major industry events and conferences, active communities and forums, and influential publications and media covering this space.", "If I'm looking to get into Analytics & BI, who and what should I know about? Include the most trusted brands, recommended products and services, reputable companies and providers, influential experts and reviewers to follow, helpful communities and resources, important events and conferences, notable startups disrupting the space, and key publications and media channels to stay informed.", "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: DJ Patil.
Used by AI Models
| Model | Voice | Position | Citations |
|---|---|---|---|
|
|
{{ getInfluenceForBot(bot.id) }} | {{ getPositionForBot(bot.id) }} | {{ getMentionsForBot(bot.id) }} |
Pages from en.wikipedia.org (14 links)
| URL Path | Citations | Position |
|---|---|---|
| /wiki/Cathy_O'Neil | 0 | N/A |
| /wiki/Business_intelligence | 2 | 1 |
| /wiki/SQL | 1 | 2 |
| /wiki/Data_warehouse | 1 | 3 |
| /wiki/Extract,_transform,_load | 1 | 9 |
| /wiki/Data_lakehouse | 1 | 12 |
| /wiki/Data_governance | 2 | 16 |
| /wiki/Data_quality | 1 | 20 |
| /wiki/Semantic_layer | 1 | 22 |
| /wiki/Data_visualization | 1 | 23 |
| /wiki/Thomas_H._Davenport | 1 | 108 |
| /wiki/Bill_Inmon | 1 | 112 |
| /wiki/DJ_Patil | 1 | 119 |
| /wiki/Business_intelligence_analyst | 1 | 177 |
Brands Referenced By This Website (1 brand)
| Brand | Voice | Mentions |
|---|---|---|
| DJ Patil | 0% | 1 |
Citations from AI Responses
Anthropic Claude Sonnet (latest)
(1 citation)
What are the best Analytics & BI options available today? Please provide a comprehensive overview including: the leading brands and products, top companies and service providers, recognized experts and thought leaders, promising startups and new market entrants, major industry events and conferences, active communities and forums, and influential publications and media covering this space.
[...] us 49. **[Andy Kirk](https://www.visualisingdata.com/)** - Data visualization specialist - Author and trainer - Visualising Data blog 50. **[Brent Dykes](https://www.effectivedatastorytelling.com/)** - Effective Data Storytelling - Author and consultant - Forbes contributor 51. **[DJ Patil](https://en.wikipedia.org/wiki/DJ_Patil)** - Former US Chief Data Scientist - Data science thought leader 52. **[Caitlin Smallwood](https://www.netflix.com/)** - VP of Science & Algorithms at Netflix - Analytics innovation leader 53. **[Hilary Mason](https://hilarymason.com/)** - Data scientist and entrepreneur - Co-founder [...]
OpenAI ChatGPT Latest
(14 citations)
What are the best Analytics & BI options available today? Please provide a comprehensive overview including: the leading brands and products, top companies and service providers, recognized experts and thought leaders, promising startups and new market entrants, major industry events and conferences, active communities and forums, and influential publications and media covering this space.
[...] es, people, events, communities, and media). Because “best” depends heavily on your stack (Microsoft/AWS/GCP/Snowflake/Databricks), governance needs, and whether you want self-service BI vs. embedded/operational analytics, I’ve grouped options by common buying patterns. For background terminology: [Business intelligence (BI)](https://en.wikipedia.org/wiki/Business_intelligence) --- ## 1) Leading BI & Analytics products (established “top of market”) ### Broad enterprise BI (common shortlists) - [Microsoft Power BI](https://powerbi.microsoft.com/) (often best if you’re Microsoft 365/Azure-first; strong price/value) - [Tableau](https://www.tableau.com/) (strong visual ex [...]
[...] - [Infosys](https://www.infosys.com/) Specialist research/training orgs that many BI teams use: - [TDWI](https://tdwi.org/) - [Dresner Advisory Services](https://www.dresneradvisory.com/) --- ## 5) Recognized experts & thought leaders (good signals for methods, governance, org design) - [Thomas H. Davenport](https://en.wikipedia.org/wiki/Thomas_H._Davenport) (analytics strategy, management) - [Ralph Kimball](https://en.wikipedia.org/wiki/Ralph_Kimball) (dimensional modeling; enduring BI design influence) - [Bill Inmon](https://en.wikipedia.org/wiki/Bill_Inmon) (data warehouse concepts) - [Howard Dresner](https://en.wikipedia.org/wiki/Howard_Dresner) ( [...]
[...] rts & thought leaders (good signals for methods, governance, org design) - [Thomas H. Davenport](https://en.wikipedia.org/wiki/Thomas_H._Davenport) (analytics strategy, management) - [Ralph Kimball](https://en.wikipedia.org/wiki/Ralph_Kimball) (dimensional modeling; enduring BI design influence) - [Bill Inmon](https://en.wikipedia.org/wiki/Bill_Inmon) (data warehouse concepts) - [Howard Dresner](https://en.wikipedia.org/wiki/Howard_Dresner) (BI industry analyst; [Dresner Advisory Services](https://www.dresneradvisory.com/)) - [Wayne Eckerson](https://www.eckerson.com/) (BI/data strategy; research & education) - [Avinash Kaushik](https://www.kau [...]
If I'm looking to get into Analytics & BI, who and what should I know about? Include the most trusted brands, recommended products and services, reputable companies and providers, influential experts and reviewers to follow, helpful communities and resources, important events and conferences, notable startups disrupting the space, and key publications and media channels to stay informed.
## 1) Core concepts to get fluent in (the “what”) - **Business intelligence (BI)**: reporting + dashboards for decisions — [Wikipedia: Business intelligence](https://en.wikipedia.org/wiki/Business_intelligence) - **Analytics** (descriptive → predictive) — [Wikipedia: Analytics](https://en.wikipedia.org/wiki/Analytics) - **SQL** (non‑negotiable) — [Wikipedia: SQL](https://en.wikipedia.org/wiki/SQL) - **Data warehousing** — [Wikipedia: Data warehouse](https://en.wikipedia.org/wiki/Data_warehouse) - [...]
[...] *Business intelligence (BI)**: reporting + dashboards for decisions — [Wikipedia: Business intelligence](https://en.wikipedia.org/wiki/Business_intelligence) - **Analytics** (descriptive → predictive) — [Wikipedia: Analytics](https://en.wikipedia.org/wiki/Analytics) - **SQL** (non‑negotiable) — [Wikipedia: SQL](https://en.wikipedia.org/wiki/SQL) - **Data warehousing** — [Wikipedia: Data warehouse](https://en.wikipedia.org/wiki/Data_warehouse) - **Dimensional modeling** (star schemas, facts/dimensions) — [Kimball Group](https://www.kimballgroup.com/) - **ETL / ELT** — [Wikipedia: Extract, transform, load](https://en.wikipedia.org/wik [...]
[...] ct,_transform,_load) - **Semantic layer / metrics layer** (consistent business definitions) — [dbt Semantic Layer docs](https://docs.getdbt.com/docs/use-dbt-semantic-layer) - **Data governance** — [Wikipedia: Data governance](https://en.wikipedia.org/wiki/Data_governance) - **Data quality** — [Wikipedia: Data quality](https://en.wikipedia.org/wiki/Data_quality) - **Data visualization** (perception, chart choices, storytelling) — [Wikipedia: Data visualization](https://en.wikipedia.org/wiki/Data_visualization) --- ## 2) Most trusted brands (BI & dashboarding) These are the most common “default choices” you’ll run into in real orgs: - **Microsoft Po [...]
[...] .com/docs/use-dbt-semantic-layer) - **Data governance** — [Wikipedia: Data governance](https://en.wikipedia.org/wiki/Data_governance) - **Data quality** — [Wikipedia: Data quality](https://en.wikipedia.org/wiki/Data_quality) - **Data visualization** (perception, chart choices, storytelling) — [Wikipedia: Data visualization](https://en.wikipedia.org/wiki/Data_visualization) --- ## 2) Most trusted brands (BI & dashboarding) These are the most common “default choices” you’ll run into in real orgs: - **Microsoft Power BI** — [Power BI](https://powerbi.microsoft.com/) - **Tableau** — [Tableau](https://www.tableau.com/) - **Qlik** — [Qlik](https://www.qlik.com/) [...]
[...] www.forrester.com/) - **G2** (crowd reviews) — [G2](https://www.g2.com/) - **Capterra** (reviews) — [Capterra](https://www.capterra.com/) --- ## If you tell me 3 things, I can tailor a “who/what to learn” map 1) Your target role: **BI analyst**, **analytics engineer**, or **BI developer** — [Wikipedia: Business intelligence analyst](https://en.wikipedia.org/wiki/Business_intelligence_analyst) 2) Your likely ecosystem: **Microsoft** ([Microsoft](https://www.microsoft.com/)), **Google Cloud** ([Google Cloud](https://cloud.google.com/)), **AWS** ([AWS](https://aws.amazon.com/)) 3) Your industry (finance/health/ecomm/SaaS/etc.) Then I’ll suggest a tight learning path (tools + projects [...]
[...] com/) - **ETL / ELT** — [Wikipedia: Extract, transform, load](https://en.wikipedia.org/wiki/Extract,_transform,_load) - **Semantic layer / metrics layer** (consistent business definitions) — [dbt Semantic Layer docs](https://docs.getdbt.com/docs/use-dbt-semantic-layer) - **Data governance** — [Wikipedia: Data governance](https://en.wikipedia.org/wiki/Data_governance) - **Data quality** — [Wikipedia: Data quality](https://en.wikipedia.org/wiki/Data_quality) - **Data visualization** (perception, chart choices, storytelling) — [Wikipedia: Data visualization](https://en.wikipedia.org/wiki/Data_visualization) --- ## 2) Most trusted brands (BI & dashboarding [...]
[...] a: Business intelligence](https://en.wikipedia.org/wiki/Business_intelligence) - **Analytics** (descriptive → predictive) — [Wikipedia: Analytics](https://en.wikipedia.org/wiki/Analytics) - **SQL** (non‑negotiable) — [Wikipedia: SQL](https://en.wikipedia.org/wiki/SQL) - **Data warehousing** — [Wikipedia: Data warehouse](https://en.wikipedia.org/wiki/Data_warehouse) - **Dimensional modeling** (star schemas, facts/dimensions) — [Kimball Group](https://www.kimballgroup.com/) - **ETL / ELT** — [Wikipedia: Extract, transform, load](https://en.wikipedia.org/wiki/Extract,_transform,_load) - **Semantic layer / metrics layer** (consistent business definitions) [...]
[...] n‑negotiable) — [Wikipedia: SQL](https://en.wikipedia.org/wiki/SQL) - **Data warehousing** — [Wikipedia: Data warehouse](https://en.wikipedia.org/wiki/Data_warehouse) - **Dimensional modeling** (star schemas, facts/dimensions) — [Kimball Group](https://www.kimballgroup.com/) - **ETL / ELT** — [Wikipedia: Extract, transform, load](https://en.wikipedia.org/wiki/Extract,_transform,_load) - **Semantic layer / metrics layer** (consistent business definitions) — [dbt Semantic Layer docs](https://docs.getdbt.com/docs/use-dbt-semantic-layer) - **Data governance** — [Wikipedia: Data governance](https://en.wikipedia.org/wiki/Data_governance) - **Data quality** — [Wikipedia: Data qu [...]
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.
[...] 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_lakehouse)) and formats like [Apache Iceberg](https://iceberg.apache.org/), [Delta Lake](https://delta.io/), and [Apache Hudi](https://hudi.apache.org/). - **Metrics/semantic layer focus**: reducing metric inconsistency and “dashboard drift” via centralized definitions (see [Semantic layer (Wikipedia)](https [...]
[...] .wikipedia.org/wiki/Data_lakehouse)) and formats like [Apache Iceberg](https://iceberg.apache.org/), [Delta Lake](https://delta.io/), and [Apache Hudi](https://hudi.apache.org/). - **Metrics/semantic layer focus**: 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)). - **Govern [...]
[...] re 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,” many buyers look to analyst evaluations such as the [Gartner Magic Quadrant for Analytics and BI Platforms](https://www.gartner.com/en/research/magic-quadrant) (landing page) and [Forrester Research](https://www.forrester.com/). --- ## 2) Dominant market leaders & brands (by [...]