Evaluate data quality.

Evaluate data quality. is a detailed work activity in O*NET — a concrete unit of work shared across 8 occupations and seen in 11 occupation-specific tasks. It rolls up into the broader work activity Evaluate the quality or accuracy of data. in Processing Information .

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 11 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 11 (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 7 of these tasks, with a mean mapped-usage share of 0.068% 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.

• Define data requirements, and gather and validate information, applying judgment and statistical tests. · Operations Research Analysts · importance 4.5 · exposure with tools
• Design and validate clinical databases, including designing or testing logic checks. · Clinical Data Managers · importance 4.5 · direct LLM exposure
• Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data. · Statisticians · importance 4.5 · direct LLM exposure
• Verify the structure, accuracy, or quality of warehouse data. · Data Warehousing Specialists · importance 4.4 · exposure with tools
• Process clinical data, including receipt, entry, verification, or filing of information. · Clinical Data Managers · importance 4.4 · exposure with tools
• Verify integrity and accuracy of data contained in remote sensing image analysis systems. · Remote Sensing Technicians · importance 4.2 · exposure with tools
• Evaluate sources of information to determine any limitations, in terms of reliability or usability. · Statisticians · importance 4.1 · exposure with tools
• Review existing or incoming data for currency, accuracy, usefulness, quality, or completeness of documentation. · Geographic Information Systems Technologists and Technicians · importance 4.1 · exposure with tools
• Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data. · Clinical Data Managers · importance 3.7 · exposure with tools
• Plan, conduct, and evaluate nutrigenomic or nutrigenetic research. · Dietitians and Nutritionists · importance 3.1 · exposure with tools
• Perform quality control checks on data to be used by hydrologists. · Hydrologic Technicians · exposure with tools

Occupations that perform this

• Operations Research Analysts
• Clinical Data Managers
• Statisticians
• Data Warehousing Specialists
• Remote Sensing Technicians
• Geographic Information Systems Technologists and Technicians
• Dietitians and Nutritionists
• Hydrologic Technicians

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-evaluate-data-quality,
  title  = {Evaluate data quality.},
  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/evaluate-data-quality}
}