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Project Overview

This project analyzes four months of sales and customer activity for J&SONS Farm, focusing on fish-type performance, customer behavior, and month-to-month volume trends. Using Power Query, DAX, and Power BI, the raw farm records were transformed into a structured analytical model that reveals growth patterns, top buyers, and key revenue drivers in the aquaculture business.

Process & Methodology

Data Cleaning & Transformation (Power Query)
Raw transactional records were manually cleaned, standardized, and validated. Product categories were unified into Mixed, Post, Standard, and Juvenile. Duplicates, inconsistent dates, and missing quantities were resolved to ensure accurate aggregation.

Data Modeling & KPI Development (DAX)
A streamlined star-model was created, enabling month-level analysis, customer segmentation, and product category comparison. Core KPIs (Total Units Sold, Customer Count, Transaction Count, and Month-over-Month (MoM) Growth) were built with DAX.

Visualization & Insight Design
Interactive Power BI visuals were developed:

• Monthly sales trend

• Fish-type performance

• Customer ranking table

• Transaction count by month

This structure highlights the business drivers and allows quick comparison across months.

Business Questions

• How strong is monthly sales growth within the four-month period?

• Which fish categories contribute most to total volume?

• Who are the highest-value customers?

• How evenly are transactions and quantities distributed across the months?

• What early trends indicate opportunities for growth or risks of over-dependence?

Objectives

• Quantify growth and validate the 101.88% MoM surge.

• Identify top contributors among fish categories and customers.

• Understand customer concentration and purchasing behavior.

• Provide a clear summary of sales trends for leadership decision-making.

Key Insights & Findings

Growth & Volume Performance

• Total Units Sold: 1,392,148

• Customer Count: 51

• Transactions: 162

• The business recorded a 101.88% month-over-month increase, indicating a major spike in demand.

• Sales peaked in June (690K units) before dropping to 482K in July.

Monthly Trend (April → July)

• April: 108K

• May: 113K

• June: 690K (peak)

• July: 482K
  The data shows a sharp growth curve into June, followed by a correction in July.

Fish-Type Performance

• Mixed fish type dominates the dataset at 0.66M units.

• Post follows at 0.38M, then Standard (0.23M) and Juvenile (0.10M).
  Mixed is the clear volume leader and key to revenue stability.

Customer Insights

• Top Buyer: Bro Oye, 477,958 units, far exceeding every other customer.

• Other customers contribute far smaller shares.
  This reveals strong customer concentration, where one buyer accounts for a disproportionately large share of total volume.

Transaction Patterns

• July recorded the highest number of transactions (84) but not the highest quantity.

• June had fewer transactions but extremely high quantities, indicating bulk-order behavior in that month.

Recommendations

• Validate June spike: Confirm if the surge reflects market demand, promotional sales, or bulk one-off orders.

• Monitor customer concentration: Track Bro Oye’s monthly contribution and diversify the customer base to reduce single-buyer dependency.

• Deepen product-type analysis: Evaluate margins by fish category to understand whether volume aligns with profitability (if cost data becomes available).

• Create monthly forecasts: Establish a short-term forecasting model to anticipate high-volume months and plan data-driven decision-making.

• Expand dashboard KPIs: Add revenue, unit price, and customer tenure to improve future insight depth.

Expected Impact

• Stronger understanding of growth patterns and month-to-month volatility.

• Improved strategic focus on high-value customers and high-volume fish categories.

• Better data visibility for planning, reporting, and commercial decisions within the aquaculture business.