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Machine Learning · ML-14

Entrepreneurship Transition Prediction

Model transitions from education or employment into synthetic business ownership using dated resident histories.

  • Synthetic records
  • Longitudinal
  • Nairobi + Lagos
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Scope & purpose

Connected scope

Connect work, education, household context and business formation to explore entry into entrepreneurship.

  • Employment
  • Education
  • Business
  • Households

Define the prediction date and horizon. Keep earlier inputs separate from later outcomes.

Possible uses

Prediction prototyping · Feature exploration · Temporal validation · Cohort comparison

Who it is for

Economists · business analysts · ML teams · market researchers

Preview type
Illustrative format preview
Shows example structure and fields. It is not a sample extracted from the paid release.
Commercial availability
Confirmed in your written quote
The listed cities describe catalogue coverage. We confirm the exact release and available extract before agreement.
Starting-price basis
USD per selected city
Cohort size and period are specified in the quote; the listed rate does not define a fixed-size package. Discount and tax are shown separately.
Your agreed delivery
Scope and supporting artifacts listed in the quote
Confirm entities or rows, observation period, fields, formats, documentation, evidence, known limits and usage rights.

Paid dataset delivery

What you receive

SD delivery standard
Published cities
Nairobi + Lagos
Record scope
Resident-level
Structure
Longitudinal

Striped Donkey delivery package

  • data/Agreed extract and formats
  • documentation/Schema, fields and relationships
  • evidence/Agreed release checks and limits
  • examples/Agreed loading and join examples
  • LICENSEApplicable rights
  • MANIFESTRelease and file inventory
  • CHECKSUMSSHA-256 fingerprints
  • DELIVERY_NOTEScope and handoff record

Your written quote confirms selected cities, period, formats, commercial rights, detailed artifacts and secure delivery. The complete paid package is prepared privately after agreement.

Free evaluation preview

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15 illustrative rows · 11 fields · CSV

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Illustrative rows show the format. Your quote confirms delivered records, fields and time coverage.

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Fields and record structure

Listed features

Resident-level · Longitudinal

  • business formation date
  • prior employment
  • education background
  • employment spells
  • employer / work transitions
  • earnings context
  • enrolment history

Study question

Evaluation design

Can earlier education, employment and household histories predict who enters recorded business ownership within the next 24 months?

Define an eligible non-owner cohort and dated owner-to-business links; prevent leakage from future business records and retain incomplete observation.

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Evidence you can inspect

Source & limitations

Review release-specific methods and published checks. Preview rows show format and scope; they do not certify a dataset.

Supporting references
NairobiEvidenceSamples
LagosEvidenceSamples
MethodsGenerationReproduce

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Licence & delivery

Free preview

Use free samples under the public-use policy or their dataset-specific licence. Attribution is required for publication and research outputs.

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Purchased dataset

Your agreement defines the release, licensed organization, permitted uses and duration. Commercial model training, external applications and redistribution require explicit agreement.

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