Prepare data for analysis.

Prepare data for analysis. is a detailed work activity in O*NET — a concrete unit of work shared across 6 occupations and seen in 12 occupation-specific tasks. It rolls up into the broader work activity Process digital or online data. in Working with Computers .

Detailed work activities are the most granular shared layer in O*NET's work-activity hierarchy (Generalized → Intermediate → Detailed → occupation-specific task). The figures below describe how this activity shows up across the economy and what independent studies measure about AI and this kind of work — not a prediction that the work will be automated.

AI exposure

Of the 12 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 12 (100%) are flagged as directly exposed to language models (E1) or exposed via model-powered tools (E2).

The Anthropic Economic Index observes real AI use on 5 of these tasks, with a mean mapped-usage share of 0.038% per task.

Exposure estimates overlap with model capabilities — whether a model could speed the task up — not whether the work will be done by software. Observed AI use is augmentation and assistance today, not jobs replaced.

Member tasks

Occupation-specific tasks O*NET maps to this detailed work activity, most important first.

• Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data. · Statisticians · importance 4.5 · direct LLM exposure
• Process clinical data, including receipt, entry, verification, or filing of information. · Clinical Data Managers · importance 4.4 · exposure with tools
• Assist in the development of document or content classification taxonomies to facilitate information capture, search, and retrieval. · Document Management Specialists · importance 4.3 · direct LLM exposure
• Identify and classify documents or other electronic content according to characteristics such as security level, function, and metadata. · Document Management Specialists · importance 4.2 · exposure with tools
• Process large amounts of data for statistical modeling and graphic analysis, using computers. · Statisticians · importance 4.0 · direct LLM exposure
• Prepare appropriate formatting to data sets as requested. · Clinical Data Managers · importance 4.0 · direct LLM exposure
• Collect, compile, or integrate Geographic Information Systems (GIS) data, such as remote sensing or cartographic data for inclusion in map manuscripts. · Geographic Information Systems Technologists and Technicians · importance 3.9 · exposure with tools
• Code data in preparation for computer entry. · Social Science Research Assistants · importance 3.9 · direct LLM exposure
• Create, analyze, report, convert, or transfer data, using specialized applications program software. · Geographic Information Systems Technologists and Technicians · importance 3.7 · exposure with tools
• Store, retrieve, and manipulate data for analysis of system capabilities and requirements. · Software Developers · importance 3.6 · direct LLM exposure
• Clean and manipulate raw data using statistical software. · Data Scientists · direct LLM exposure
• Store, retrieve, and manipulate data for analysis of system capabilities and requirements. · Software Quality Assurance Analysts and Testers · direct LLM exposure

Occupations that perform this

• Statisticians
• Clinical Data Managers
• Document Management Specialists
• Social Science Research Assistants
• Software Developers
• Software Quality Assurance Analysts and Testers

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
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-prepare-data-for-analysis,
  title  = {Prepare data for analysis.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/detailed-activities/prepare-data-for-analysis}
}