Course overview
Agriculture programmes, farms and agribusinesses generate large volumes of data on production, inputs, rainfall, markets, beneficiaries, livestock, field visits and budgets. Yet this information is often held in disconnected spreadsheets with inconsistent farmer names, mixed units, missing values and formulas that cannot be checked. Staff need to turn operational records and survey extracts into reliable analysis for planting decisions, input planning, donor reporting, procurement, credit assessment and programme management.
This five-day course develops practical Microsoft Excel methods for agricultural data work. Participants organise farm and programme datasets, clean survey exports, apply validation controls, calculate yields and gross margins, join records with XLOOKUP, analyse trends through PivotTables, and build clear reports and dashboards. The course also covers seasonal cash-flow analysis, indicator tracking, data-quality checks, descriptive statistics and scenario analysis for crop and livestock enterprises.
Teaching combines concise technical briefings with agriculture-based cases, guided spreadsheet work, group analysis and reporting simulations. Cases may include smallholder farmer registers, crop-cut data, input distribution records, market-price series, extension-service monitoring and enterprise budgets. Participants leave with an agriculture data-analysis workbook pack containing reusable templates, formula patterns, reporting structures and an application plan for improving one live workplace dataset.
The course suits professionals working in agricultural development, commercial farming, cooperatives, agribusiness, food security programmes, rural finance and agricultural supply chains. It is particularly useful for staff responsible for converting field data into evidence that managers, funders, farmers and operational teams can act on.
