[{"data":1,"prerenderedAt":162},["ShallowReactive",2],{"site":3,"work:\u002Fwork\u002Fnaro-big-data-platform":21,"work-order":151},{"id":4,"availability":5,"cvEnabled":6,"cvPath":7,"email":8,"extension":9,"github":10,"hmtUrl":11,"intro":12,"linkedin":13,"location":14,"meta":15,"name":16,"positioning":17,"roleLabel":18,"stem":19,"__hash__":20},"site\u002Fdata\u002Fsite.yml","Based in Kampala. Available for projects in Uganda and remotely.",false,"\u002Fcv\u002Fbarlow-kasule-cv.pdf","Barlow.kasule@outlook.com","yml","https:\u002F\u002Fgithub.com\u002Fkasbaros","","I lead the data and AI function at FutureLink Technologies, a Kampala fintech, and I have built web systems since 2018 for fintechs, national research and statistics bodies, schools and private companies. You get one engineer who can design, build and run both the product and the data behind it.","https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fkasulebarlow1989\u002F","Kampala, Uganda",{},"Barlow Kasule","I build the whole system, from the web app and mobile-money integration to the data pipelines and ML models behind it.","Data & software consultant","data\u002Fsite","wyvEemA03cYJSTnIor0Et6BCchMTuA22lW5uyID8iJ4",{"id":22,"title":23,"body":24,"description":127,"extension":128,"meta":129,"navigation":130,"order":131,"path":132,"period":133,"role":134,"sector":135,"seo":136,"stack":137,"status":145,"stem":146,"subtitle":147,"tags":148,"__hash__":150},"work\u002Fwork\u002Fnaro-big-data-platform.md","NARO Big Data Platform",{"type":25,"value":26,"toc":119},"minimark",[27,32,36,40,43,47,51,92,96,101,112,116],[28,29,31],"h2",{"id":30},"context","Context",[33,34,35],"p",{},"The National Agricultural Research Organisation (NARO) coordinates agricultural research across its Secretariat and 16 public research institutes, including Namulonge and Kawanda. Research data, from field trials to institutional databases, lived on personal laptops and external drives, with no shared storage or consistent backup. NARO set out to build a Big Data Centre and analytics platform to serve all 16 institutes.",[28,37,39],{"id":38},"role","Role",[33,41,42],{},"Consultant, Data Science & Engineering (part-time). I led the data analysis workstream within a 10-person multidisciplinary team of M&E specialists, statisticians and agricultural specialists, and co-authored the original concept note.",[28,44,46],{"id":45},"what-i-did","What I did",[48,49],"timeline-strip",{":items":50},"[{\"when\":\"2022\",\"title\":\"Round one\",\"detail\":\"Concept note, benchmarking visits, needs assessment across the institutes, analytical report and budget.\"},{\"when\":\"Early 2025\",\"title\":\"Round two\",\"detail\":\"Redone with new funding: more institutions, more detail, better evidence. Cut short when donor funding was withdrawn.\"},{\"when\":\"Next\",\"title\":\"Architecture decision\",\"detail\":\"On-premise, in-country hosting proposed; decision pending.\"}]",[52,53,54,62,68,74,80,86],"ul",{},[55,56,57,61],"li",{},[58,59,60],"strong",{},"Requirements from the field."," Fieldwork tours and stakeholder workshops across the NARO institutions, working with technicians, researchers, non-technical staff, scientists and leadership to gather requirements and document use cases and process flows.",[55,63,64,67],{},[58,65,66],{},"Evidence from the surveys."," I analysed the needs-assessment surveys (in round one, 62 staff on their data practices and 19 institute ICT infrastructure audits) and wrote the analytical report the budget and requirements were built on.",[55,69,70,73],{},[58,71,72],{},"Requirements and specifications."," Business requirements documents and system specifications for a unified data architecture.",[55,75,76,79],{},[58,77,78],{},"Architecture roadmap."," The target ecosystem is Apache Hadoop, Spark and Hive, ingesting structured and unstructured data (field research datasets, institutional databases), sized for a projected 20TB+ across the Secretariat and the 16 institutes.",[55,81,82,85],{},[58,83,84],{},"Cost-benefit and deployment."," Feasibility studies and cost-benefit analyses of technology stacks and of cloud against on-premise deployment, with forecasts for infrastructure, licensing and maintenance. The 2022 concept note recommended a managed-cloud data centre built around a data lake as a fast start. The fuller 2025 evidence pointed to on-premise, in-country hosting.",[55,87,88,91],{},[58,89,90],{},"Proposals that secured approval."," Project proposals covering requirements, technical approach, resource estimates, timelines and budgets that won stakeholder approval for the initiative.",[28,93,95],{"id":94},"what-the-field-evidence-showed","What the field evidence showed",[97,98],"stat-cards",{":items":99,"caption":100},"[{\"value\":\"48 of 62\",\"label\":\"had no one responsible for data storage in their unit\"},{\"value\":\"0 of 53\",\"label\":\"backed up research data to an institute server\"},{\"value\":\"11 of 60\",\"label\":\"generated more than 100 GB of data a year each\"},{\"value\":\"36 of 45\",\"label\":\"of those who knew cloud storage agreed with using it\"}]","Round-one needs assessment, 62 staff across the institutes. Each figure is out of those who answered that question.",[52,102,103,106,109],{},[55,104,105],{},"About a third relied on consumer cloud drives for backups.",[55,107,108],{},"Infrastructure gaps included missing or makeshift server rooms, no system administrators at some institutes, low-end workstations and weak connectivity at remote stations.",[55,110,111],{},"Some staff feared losing control of their data once it was centralised, so governance and access rules had to be part of the design from the start.",[28,113,115],{"id":114},"outcome","Outcome",[33,117,118],{},"Two rounds of requirements and design are complete, and the evidence moved the deployment recommendation from a managed cloud to on-premise, in-country hosting. The architecture decision is pending; the project paused after donor funding was cut in 2025.",{"title":11,"searchDepth":120,"depth":120,"links":121},2,[122,123,124,125,126],{"id":30,"depth":120,"text":31},{"id":38,"depth":120,"text":39},{"id":45,"depth":120,"text":46},{"id":94,"depth":120,"text":95},{"id":114,"depth":120,"text":115},"Requirements, survey evidence, architecture roadmap and costed proposals for a data platform serving NARO's Secretariat and 16 research institutes.","md",{},true,4,"\u002Fwork\u002Fnaro-big-data-platform","2022 – 2025","Consultant, Data Science & Engineering · led the data analysis workstream","Research",{"title":23,"description":127},[138,139,140,141,142,143,144],"Hadoop","Spark","Hive","Data-lake design","Survey design & analysis","Capacity forecasting","Cost-benefit analysis","Two rounds of requirements and design; architecture decision pending (on-premise, in-country proposed); paused after donor funding was cut in 2025.","work\u002Fnaro-big-data-platform","Laying the groundwork for a national agricultural research data platform across 16 institutes, from field requirements to architecture roadmap and budget",[138,139,140,149],"Field research","PDcQG4a-8Tdn6XVtCs4GuNtSJkm6x7ml91fj_F46pbI",[152,155,158,159],{"path":153,"title":154},"\u002Fwork\u002Fflt-analytics-platform","FLT Analytics Platform",{"path":156,"title":157},"\u002Fwork\u002Fschoolplus","SchoolPlus",{"path":132,"title":23},{"path":160,"title":161},"\u002Fwork\u002Fubos-and-ug-registry","UBOS Gender Statistics Portal & .UG registry",1790854436824]