• Other
  • 27 columns
  • 76 rows
  • 8 formats

Nonprofit Donation Impact Tracking

This dataset provides a transparent, end-to-end view of nonprofit donations, tracing each contribution from individual or organizational donors through project allocations to quantifiable social impact outcomes. It enables NGOs, donors, and stakeholders to analyze fund distribution efficiency, measure real-world results, and optimize strategies for maximizing social good.

  • last updated 29 Jan 2026
  • by GoMask
The brief that made it

Donor transparency and reporting for NGOs

Sample rows

preview · 8 of 76 rows · all 27 columns
donation_idstringdonor_typestringdonation_amountfloatimpact_metricstringdonor_idstringdonor_namestringdonor_emailstringdonor_phonestringdonor_address_streetstringdonor_address_citystringdonor_address_statestringdonor_address_postal_codestringdonor_address_countrystringproject_idstringproject_namestringproject_categorystringproject_location_citystringproject_location_statestringproject_location_countrystringdonation_currencystringdonation_datedateallocation_percentagefloatimpact_valuefloatimpact_unitstringimpact_reported_datedatengo_idstringngo_namestring
D100001individual250meals_providedINDV001Maria Gonzalesmaria.gonzales@gmail.com+1-213-555-17231245 Maple AveLos AngelesCA90015USAPRJ001Healthy Kids LAhealthLos AngelesCAUSAUSD2023-02-15100500meals2023-04-05NGO001Feeding Futures
D100002organization1200trees_plantedORG101GreenEarth Corpdonations@greenearth.com+44-20-7946-003888 Regent StLondonGreater LondonW1B 5RLUKPRJ002Urban Tree RevivalenvironmentLondonGreater LondonUKGBP2022-11-03100180trees2023-02-01NGO002Earth Roots Foundation
D100003individual75.5children_educatedINDV002Andrew Chenandrew.chen@outlook.com+65-8123-993356 Bukit Timah RdSingaporeCentral229837SingaporePRJ003Teach to ReacheducationSingaporeCentralSingaporeSGD2023-01-1010012children2023-03-22NGO003Bright Future Initiative
D100004organization550vaccines_administeredORG102Wellness Unitedcontact@wellnessunited.org+49-30-4000-200012 FriedrichstrasseBerlinBerlin10117GermanyPRJ004Health for AllhealthBerlinBerlinGermanyEUR2023-03-07100330vaccines2023-05-18NGO004Global Wellness Network
D100005individual300liters_water_suppliedINDV003Olivia Martinolivia.martin@icloud.com+61-2-5552-203323 King StSydneyNSW2000AustraliaPRJ005Clean Water AccessenvironmentSydneyNSWAustraliaAUD2022-09-2510012000liters2022-11-20NGO005Water for Life
D100006organization2000students_trainedORG103Tech4Changedonate@tech4change.com+1-415-555-9087500 Market StSan FranciscoCA94105USAPRJ006Digital Learning LabeducationSan FranciscoCAUSAUSD2023-04-0910085students2023-06-14NGO006Learning Forward
D100007individual150kits_distributedINDV004Samuel Patelsam.patel@yahoo.com+91-99303-45678B-401 Lotus ApartmentsMumbaiMH400012IndiaPRJ007School Supplies DriveeducationMumbaiMHIndiaINR2023-05-2210070kits2023-06-30NGO007Children First Trust
D100008organization850meals_providedORG104FoodShare Incgive@foodshare.org+1-646-555-908777 BroadwayNew YorkNY10006USAPRJ008NYC Hunger ReliefhealthNew YorkNYUSAUSD2022-08-041001700meals2022-10-18NGO008Care for All

What the 76 rows show

from the 76-row sample

Individual (donor type) stands out: mean donation_amount is 385.8, against 1,132 for the rest.

  • 670.0median donation_amount
  • 4project categories
  • 21donation currencies
  • 22impact units
  • 90median impact_value
Mean donation_amount by donor_type76 rows
01,0002,000385.8individual38 rows1,132organization38 rows
donation_amount76 rows, in bands of 250
0153072411139342301,2502,250donation_amount →

Median 670.0, from 75.5 to 2,200.

impact_metric76 rows · top 10 of 28 values
  1. meals_provided14
  2. trees_planted9
  3. children_educated9
  4. liters_water_supplied4
  5. students_trained4
  6. kits_distributed4
  7. vaccines_administered3
  8. kilograms_waste_removed3
  9. air_filters_distributed2
  10. books_distributed2
27 columns by typefrom the column list below
  • string 22
  • float 3
  • date 2

Columns

27 columns in three groups
blueprint · 27 columns
columntypedescriptionexample
Text 22 columns
donation_idstringUnique identifier for each donation transaction.uniqueD100001
donor_idstringUnique identifier for the donor (individual or organization).INDV001
donor_typestringSpecifies if the donor is an 'individual' or 'organization'.individual · organizationindividual
donor_namestringFull name of the individual donor or organization.Maria Gonzales
donor_emailstringEmail address of the donor (if available).optionalmaria.gonzales@gmail.com
donor_phonestringContact phone number for the donor (if available).optional+1-213-555-1723
donor_address_streetstringStreet address of the donor (if available).optional1245 Maple Ave
donor_address_citystringCity of the donor's address.optionalLos Angeles
donor_address_statestringState or province of the donor's address.optionalCA
donor_address_postal_codestringPostal or ZIP code of the donor's address.optional90015
donor_address_countrystringCountry of the donor's address.optionalUSA
project_idstringUnique identifier for the project receiving the donation.PRJ001
project_namestringName of the project receiving the donation.Healthy Kids LA
project_categorystringCategory or focus area of the project (e.g., education, health, environment).4 categorieshealth
project_location_citystringCity where the project is implemented.optionalLos Angeles
project_location_statestringState or province where the project is implemented.optionalCA
project_location_countrystringCountry where the project is implemented.optionalUSA
donation_currencystringCurrency code for the donation amount (e.g., USD, EUR, INR).USD
impact_metricstringType of impact measured (e.g., meals_provided, children_educated, trees_planted).meals_provided
impact_unitstringUnit of the impact value (e.g., meals, children, trees).meals
ngo_idstringUnique identifier for the NGO managing the project.NGO001
ngo_namestringName of the NGO managing the project.Feeding Futures
Numbers 3 columns
donation_amountfloatMonetary value of the donation.0.01 or more250
allocation_percentagefloatPercentage of this donation allocated to the specified project (0-100).0 to 100100
impact_valuefloatQuantitative value of the impact achieved by this donation allocation.0 or more500
Dates and times 2 columns
donation_datedateDate when the donation was made.2023-02-15
impact_reported_datedateDate when the impact was reported or measured.optional2023-04-05

Use it for

  • median donatio…670.076 rowsmean donation amount …385.8indivi…1.1korgani…

    A dashboard

    Donation_amount by donor_type and a breakdown of impact_metric. Excel, Power BI or Tableau.

  • Why do the 38 individual rows have a mean donation_amount of 385.8?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable donations with donor_id, donor_type and donor_name to fill a screen in front of a buyer.

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This dataset76 rows27 columns
Yours10,000 rows27 columnsdonor_address_street: UK only

blueprint · nonprofit-donation-impact-tracking

Behind this dataset

Same schema. As many rows as you need.

These 76 rows came out of a blueprint — 27 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each donation must be linked to a project or initiative
  • Impact metrics include quantifiable outcomes (e.g., meals served, students reached)
  • Only verified donation amounts and dates are recorded
  • Project status (planned, active, completed) is tracked for every entry
  • Projects must be categorized by sector (e.g., education, health, environment)
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
nonprofit-donation-impact-tracking

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