Section Wireframe[2026-10-16 v1.7]

3. Development phase: Data pre-processing

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Why should I do this?

Address quality issues and reconstruct the dataset from the initial raw data into a format the model can use, ensuring required criteria are met. This helps ensure that the model achieves the goals established in the problem definition phase.

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Target users

  • CTOs and technical leaders
  • Data scientists and ML engineers
  • Product managers
  • Research organizations, think tanks

Checklists in play

  • Checklist 1: Risk Identification & Mitigation (Q7, Q8)
  • Checklist 3: Legal & Regulatory Compliance (Q8)

Questions to consider

Checklist 1 · Q7

How were pre-processing activities assessed to ensure they do not introduce errors or distortions that could affect outcomes?

Checklist 1 · Q8

What evidence shows that all data pre-processing steps are documented in a transparent, reproducible, and version-controlled manner?

Checklist 3 · Q8

Can data subjects (i.e., individuals whose personal data is processed) meaningfully exercise their data protection rights, including:

  1. Right to be informed;
  2. Right to rectify personal information;
  3. Right to revoke consent for personal data processing;
  4. Right to restrict data processing;
  5. Any other rights afforded under the applicable data protection laws of the country wherein the data subject resides, or where the data processor (AI developer) is incorporated.

Investment types

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Every investment project is unique

The application of the six steps will vary accordingly. To provide examples that align with your project, common characteristics of AgDev investments were researched and three ‘investment types’ were developed.

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