Zeddy Misiga
ICON Data and Learning Labs
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Zeddy Misiga is a seasoned data system specialist with a background in statistics and computer science. He possesses over 15 years of experience working across different countries designing inclusive, community-driven data and learning systems. As the Founder and Team Lead at ICON Data and Learning Labs, Zeddy leverages evidence and data to drive sustainable community transformation across Africa. He champions data governance, ethics, open data principles, and advocates for responsible use of data and AI aligned with global digital compact.
Zeddy has led more than 30 data systems initiatives with projects ranging from $10,000 to $1M collaborating with key institutions including World Bank, Commonwealth, FCDO, UNGEI, GPSDD, Duke University, Strathmore CIPIT, UN Foundation, and IREX addressing critical issues such as health, climate adaptation, education, gender equity, digital rights, and economic inclusion. He has also presented his work at global stages including, Africities Summit, International Conference on Family Planning, Africa Food Systems Forum, and African Evaluation Association (AfrEA) Conference among others.
Zeddy is a member of global networks such as the Open Data Charter, CIVICUS, Catalyst Now, and EvalForEarth, advancing data governance, digital transformation, and inclusive development across Africa. He is also an active member of the American Evaluation Association where he serves as an abstract reviewer for the annual global evaluation conference under the Research on Evaluation TIG. Additionally, he sits on the EvalForEarth, a professional network focused on evaluation for environmental sustainability and social impact. In his free time, Zeddy enjoys exploring artifacts, listening to music and cooking African cuisines.
Building the Data Quality Chain: Strengthening Hands-on Skills for Climate & Agriculture Development
Most data quality problems in sustainable development do not begin at the analysis stage. They begin earlier, when surveys are designed, when collection tools are configured, and when setting plans for what happens to the data after it is collected. The result is a persistent pattern of organisations investing significant resources in data collection for food security monitoring, climate resilience tracking, and other SDG-aligned programmes, only to discover that the data cannot support the decisions it was meant to inform. This session treats data quality as a chain. Every link matters: the survey questions, the tool configuration, the validation rules, the enumerator protocols, the cleaning workflow, the storage and access plan. If you break any single link, the entire chain fails.
Targeting practitioners working in the NGOs, research organizations, and public sector; this session will present the argument that sustainable data systems are built not through isolated tools and analytics but through end-to-end quality-by-design practices. Participants will be taken through a simplified, real-world survey workflow, from the question design to validation and cleaning using practical templates and quality checks drawn from active relevant programmes. At the end of the session, the participants will be able to diagnose weak points in their own data pipelines and apply concrete quality controls that can be implemented immediately.
IDL brings deep experience building data management and governance capacity of grassroots organisations and underserved communities across East and West Africa. On the other hand, Wrangla360 brings production-grade M&E tools and research methodology, specifically survey templates, data cleaning workflows, and quality assurance frameworks used by organisations working on food security and climate programmes. Together, we offer participants a hands-on session that equips them with additional skills to redesign data workflows, and build it into every stage of their work to inform policy, programming, and community-level decisions.
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