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Data Analysis

A data analysis AI Agent can help structure questions, inspect data, draft analysis code, and explain results. DeepAgents can support multi-step work with tasks and workspace files. The analyst remains responsible for data quality, method selection, and interpretation.

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Define the Analysis

Before providing data, state:
  • The decision or question the analysis should support
  • The meaning, units, and time range of important fields
  • Known quality issues and missing values
  • Required filters, comparison groups, and assumptions
  • The expected output format
  • Privacy or access restrictions
Do not upload data that the selected model, provider, or environment is not approved to process.

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A Reviewable Workflow

1

Inspect

Identify the file structure, field meanings, row counts, date ranges, and obvious quality issues. Do not begin with conclusions.
2

Plan

Write the proposed transformations, calculations, and checks. Use DeepAgents tasks when the work benefits from visible stages.
3

Prepare

Handle missing values, duplicates, types, and exclusions. Preserve the original input and document each change.
4

Analyze

Perform the agreed calculations. Save reusable code or queries where the configured workspace supports files.
5

Validate

Reconcile totals, inspect samples, test edge cases, and compare important calculations with an independent method.
6

Communicate

Present findings with assumptions, limitations, and enough detail for another person to reproduce the work.

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Example Request

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Using DeepAgents

DeepAgents is useful when an analysis needs a visible plan and several intermediate files. A workspace might contain:
These names illustrate an organization pattern. Actual file types and execution capabilities depend on the configured environment.

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Validation Checklist

  • Are the source, extraction time, and filters recorded?
  • Are units, currencies, time zones, and date boundaries explicit?
  • Can totals be reconciled with the source?
  • Are missing values and exclusions reported?
  • Are correlations presented without unsupported causal claims?
  • Are forecasts separated from observed results?
  • Can another analyst reproduce the transformations?
  • Has a qualified person reviewed high-impact conclusions?
Generated code and calculations can be wrong even when the explanation sounds confident. Review code before execution and verify important results independently.

DeepAgents Concepts

Understand tasks, workspace files, and review controls.

DeepAgents Workspace

Learn how to use the workspace in B-Bot Hub.

Multimodal AI

Plan workflows that use files, images, and text.

Tasks

Review the product guide for scheduled work.