Data mining software
Technology category · O*NET
Data mining software is a technology category in the O*NET database. Across U.S. occupations, 49 report using software or tools in this category. The named products below are the specific examples O*NET records for those jobs. The occupations that use it sit, on average, at the 80th percentile of AI task-exposure ( high) — how much that work overlaps with what AI can do, not a sign the tool is being replaced. See where every tool category sits.
A Hot tag marks technologies O*NET sees frequently in employer job postings; In demand marks tools an occupation specifically requires.
Example software & tools
Ranked by how many occupations list each product. Each number is an occupation count — a job is counted once per product — so the product rows overlap and do not sum to the category total.
| Software / tool | Occupations | Tags |
|---|---|---|
| Google Analytics | 35 | Hot In demand |
| Snowflake | 6 | Hot In demand |
| Data warehouse software | 2 | |
| Golden Helix HelixTree | 2 | |
| IBM Cognos Business Intelligence | 2 | |
| NCR Teradata Warehouse Miner | 2 | |
| Rapid-I RapidMiner | 2 | |
| SAP NetWeaver BW | 2 | |
| Text mining software | 2 | |
| Angoss KnowledgeSEEKER | 1 | |
| Bing for Power BI | 1 | |
| ContextMiner | 1 | |
| Cytel Software XLMiner | 1 | |
| Data extraction software | 1 | |
| Datawatch Monarch | 1 | |
| Golden Helix ChemTree | 1 | |
| IBM InfoSphere Warehouse | 1 | |
| IBM Intelligent Miner | 1 | |
| Informatica Data Explorer | 1 | |
| Oracle Darwin | 1 | |
| SAS Enterprise Miner | 1 | |
| Salford Systems CART | 1 | |
| Teradata FastLoad | 1 | |
| Teradata Parallel Transporter | 1 | |
| Teradata Tpump | 1 | |
| TokenX | 1 | |
| WizSoft WizWhy | 1 | |
| eGrabber ListGrabber | 1 |
Occupations that use Data mining software
- Accountants and Auditors
- Biochemists and Biophysicists
- Business Intelligence Analysts
- Computer Programmers
- Computer Systems Analysts
- Computer Systems Engineers/Architects
- Computer and Information Research Scientists
- Computer and Information Systems Managers
- Data Scientists
- Data Warehousing Specialists
- Database Administrators
- Database Architects
- Document Management Specialists
- Editors
- Financial Quantitative Analysts
- First-Line Supervisors of Retail Sales Workers
- Fundraising Managers
- General and Operations Managers
- Geneticists
- Historians
- Human Resources Specialists
- Information Technology Project Managers
- Intelligence Analysts
- Lawyers
- Management Analysts
- Market Research Analysts and Marketing Specialists
- Marketing Managers
- Online Merchants
- Political Science Teachers, Postsecondary
- Producers and Directors
- Property, Real Estate, and Community Association Managers
- Public Relations Managers
- Public Relations Specialists
- Real Estate Sales Agents
- Remote Sensing Technicians
- Sales Managers
- Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products
- Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products
- Search Marketing Strategists
- Secretaries and Administrative Assistants, Except Legal, Medical, and Executive
Showing 40 of 49 occupations.
How AI is used by roles that use Data mining software
A software category is not itself "being automated" — but we can look at the roles that report using Data mining software and ask how those people actually use AI. This rolls the Anthropic Economic Index per-role signal up across those roles, weighted by how much observed AI activity each one has. 57.1% of the 49 roles that use this category carry observed AI-usage data (28 roles).
Across those roles, 56.2% of AI conversations are people working with AI and 38.2% hand a task to AI , with an average autonomy of 3.67 / 5.
| Collaboration pattern | Share | What it means |
|---|---|---|
| task iteration | 38.7% | you and AI go back and forth |
| directive | 36.1% | AI does it; you give the instruction |
| learning | 12.1% | you ask AI to explain or teach |
| validation | 5.4% | you do it; AI checks your work |
| feedback loop | 2.0% | AI does it, then adjusts from your feedback |
Roles behind this signal
The roles using this category that have the most AEI data. "Works with AI" is the role's share of conversations that augment rather than automate.
| Occupation | Works with AI | Autonomy |
|---|---|---|
| Editors | 68.2% | 4.0/5 |
| Technical Writers | 54.2% | 4.0/5 |
| Political Science Teachers, Postsecondary | 65.7% | 3.3/5 |
| Secretaries and Administrative Assistants, Except Legal, Medical, and Executive | 36.3% | 3.0/5 |
| Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products | 51.1% | 3.0/5 |
| Historians | 45.3% | 4.0/5 |
| Public Relations Specialists | 65.8% | 4.0/5 |
| Statisticians | 54.2% | 4.0/5 |
| Real Estate Sales Agents | 62.2% | 3.0/5 |
| Market Research Analysts and Marketing Specialists | 47.2% | 4.0/5 |
| Online Merchants | 42.2% | 4.0/5 |
| Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products | 54.8% | 3.0/5 |
Source: Anthropic Economic Index (2026-01-15-v4-plus-2025-03-27-v2) over a sample of Claude.ai Free and Pro conversations — not all AI tools and not the whole workforce. Roles list software categories in O*NET; this does not mean AI is used inside Data mining software, only that people in those roles use AI. Some conversations are left unclassified, so shares need not sum to 100.
Industries that concentrate this
Where Data mining software matters most across the economy. Employment reach is the share of an industry's workers in occupations that significantly use Data mining software (O*NET importance ≥ 3 of 5, or report using the tool category). Concentration compares that reach to the national average industry, so a value above 1× means the requirement is more pervasive here than across the economy as a whole.
Nationally, about 13.3% of workers are in occupations that significantly use Data mining software (measured across 67 industries).
Sectors with the most such workers
| Sector | Workers | Employment reach |
|---|---|---|
| Professional, Scientific, and Technical Services | 4,493,920 | 41.7% |
| Wholesale Trade | 1,895,050 | 31.4% |
| Retail Trade | 1,858,370 | 11.9% |
| Finance and Insurance | 1,384,000 | 22.2% |
| Manufacturing | 1,309,860 | 10.3% |
| Information | 1,293,200 | 44.5% |
| Administrative and Support and Waste Management and Remediation Services | 1,078,160 | 11.9% |
| Management of Companies and Enterprises | 1,046,850 | 37.3% |
| Educational Services | 956,190 | 7.0% |
| Health Care and Social Assistance | 865,770 | 3.7% |
| Real Estate and Rental and Leasing | 741,970 | 31.3% |
| Other Services (except Public Administration) | 613,130 | 13.9% |
Industries where it is most concentrated
| Industry | Level | Concentration | Employment reach |
|---|---|---|---|
| Information | Sector | 3.35× | 44.5% |
| Television Broadcasting Stations | National industry | 3.15× | 41.9% |
| Professional, Scientific, and Technical Services | Sector | 3.14× | 41.7% |
| Management of Companies and Enterprises | Sector | 2.8× | 37.3% |
| Newspaper Publishers | National industry | 2.5× | 33.2% |
| Research and Development in the Social Sciences and Humanities | National industry | 2.49× | 33.1% |
| Wholesale Trade | Sector | 2.36× | 31.4% |
| Real Estate and Rental and Leasing | Sector | 2.35× | 31.3% |
| Radio Broadcasting Stations | National industry | 2.19× | 29.1% |
| Direct Health and Medical Insurance Carriers | National industry | 2.11× | 28.0% |
| Labor Unions and Similar Labor Organizations | National industry | 2.11× | 28.1% |
| Farm and Garden Machinery and Equipment Merchant Wholesalers | National industry | 1.96× | 26.1% |
Reach is a measure of how widespread a requirement is across an industry's workforce, not how intensively any individual uses it. Sector worker counts come from BLS OEWS employment; the significance threshold and tool use come from O*NET. Industries shown by concentration are filtered to a real worker base so a tiny specialty cannot top the list on rounding.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- Census NAICS 2022 U.S. Census Bureau
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
Data compiled June 3, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Data mining software." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026. https://singulariki.com/tools/data-mining-software
Singulariki. (2026). Data mining software. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/tools/data-mining-software
@misc{singulariki-data-mining-software,
title = {Data mining software},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026},
url = {https://singulariki.com/tools/data-mining-software}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.