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Lesson

Lesson 1: The Importance of Data Cleaning

12 September 2022

Data cleaning helps you to avoid errors during analysis, enable others to use and interpret the data, and protect the confidentiality of respondents.

Policy brief

Improving sanitation subsidy targeting: Comparing methods for identifying vulnerable households in rural Ethiopia

17 June 2025
Blog

Insights for effective SMS/IVR surveys: Lessons from the Philippines

17 June 2025
Blog

Grid-based sampling in practice

16 June 2025
News

Empowering communities through high quality, representative data

13 June 2025
Publication

Balancing rigor and cost in sampling

13 June 2025
Blog

Smarter quality at lower cost: A pragmatic framework for data quality optimization in data collection

13 June 2025
Report

Barangay Health Workers (BHWs) as RESBAKUNA Champions

13 June 2025
Project

Evaluating socio-economic outcomes of phone use by women in rural Chhattisgarh

13 June 2025
Project

Improving equity in AI for estimating household incomes

13 June 2025
Blog

Empowering Côte d’Ivoire’s Parliament to harness AI for more inclusive public policy

11 June 2025

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