Pictoquest
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Data guide · 11 min

Analyze data with AI while keeping control

AI can speed up data preparation, coding and summaries. Reliability still depends on definitions, checked calculations and a record of each transformation.

Updated 26 September 2026Read and editorially checked by Pictoquest
Two analysts compare a data table and charts on a screen.
Key points

The starting rule

Define the question, scope and units. Preserve an untouched copy of the data, request reproducible steps, then independently recalculate the results that support your conclusion.

  • Define metrics
  • Preserve source data
  • Recalculate key results

Six steps to a verifiable analysis

  1. 1. Frame the question

    State the decision, population, period, measures and meaningful comparisons. Avoid asking for a conclusion before the metrics are defined.

  2. 2. Inspect the dataset

    Check provenance, permission to use, columns, types, units, missing values, duplicates and dates. Remove or protect personal data as appropriate.

  3. 3. Preserve the source

    Work on a copy and record every filter, join and correction. Ask for a script or sequence of steps that can be rerun on the same data.

  4. 4. Check calculations

    Recalculate a few rows and the important aggregates. Compare counts, denominators, means and medians; look for edge cases and omitted categories.

  5. 5. Read the charts

    Check axes, scales, periods, legends and displayed figures. An attractive chart may hide a wrong comparison base or confuse correlation with causation.

  6. 6. Publish limitations

    Explain cleaning choices, uncertainty, missing data and tests performed. Preserve the source, script, settings and update date.

Put the method to work

Practical case

Analyse a small known table with missing values, a duplicate and a check total. Request both an answer and a chart.

Evidence to keep

Keep transformations, formulas, excluded values, independently checked calculations and chart scale choices.

Make the decision

Accept the result when another person can reproduce the numbers and explain what the chart does not show.

Compare tools on four points

Import

Which formats and volumes does the tool actually support?

Traceability

Can transformations and calculations be seen and rerun?

Control

Are errors and missing values clearly flagged?

Output

Can tables, charts and scripts be exported?

6 starting points

Tools to test on the same dataset

Compare services using a test file with missing values, duplicates and one known expected calculation. Measure the time needed to check and correct the output.

How is this selection produced?

Active services are distributed across guide-related categories, then ordered by editorial highlighting and internal score. This does not assess security, compliance or performance on your use case. Methodology.

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Frequently asked questions

Can AI replace a spreadsheet or analyst?

It can help explore and write, but definitions, methods and results still require review.

How do I verify an AI-generated chart?

Recreate aggregates from source data and compare axes, categories, units and scale with the visual.

What should be kept to reproduce the analysis?

The dated source, cleaning rules, script or steps, settings and output versions.

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