UK Exports Performance & Forecasting Dashboard

Project Overview

This project involved developing an end-to-end business intelligence solution to analyze and forecast UK export performance. The goal was to move beyond static historical reporting by integrating a predictive model, allowing stakeholders to track current performance against a data-driven forecast and identify key growth drivers, top trading partners, and emerging trends.

Python Pandas Prophet Power BI DAX Power Query Time Series

Project Objective

The goal of this project was to develop an end-to-end business intelligence solution to analyze and forecast UK export performance. I aimed to move beyond static historical reporting by integrating a predictive model, allowing stakeholders to track current performance against a data-driven forecast and identify key growth drivers, top trading partners, and emerging trends.

Technical Stack

Data Processing & Forecasting: Python (Pandas, Prophet)
Data Modeling & Visualization: Microsoft Power BI (DAX, Power Query)

My Process

1. Data Cleaning & Preparation (Python)

I began by sourcing and cleaning the raw export data using a Python script with the Pandas library. This involved transforming the data from a wide to a long format, handling missing values, and aggregating it to a consistent monthly granularity suitable for analysis.

2. Predictive Forecasting (Python)

I implemented the Prophet library to generate a 12-month forecast for key export markets. I chose this time-series model for its ability to effectively handle the strong seasonality present in the trade data.

3. Data Modeling (Power BI)

Within Power BI, I designed and implemented an optimized star schema. This involved creating a central FactExports table and dedicated Date and Country dimension tables to ensure high performance and enable robust time intelligence calculations.

4. Dashboard Development (Power BI)

I wrote a series of complex DAX measures to calculate key business metrics, including Month-over-Month Growth, Year-over-Year Growth, and Rolling 12-Month Exports. I then designed a multi-page, interactive dashboard with a professional color scheme and layout to present these findings in a clear and compelling way.

Key Outcomes & Insights

12

Month Forecast

Multi-Page

Interactive Dashboard

Star Schema

Optimized Data Model

Real-Time

Performance Tracking

Key Insights Delivered:

Performance Overview: The dashboard provides a clear, at-a-glance view of key performance indicators, immediately highlighting the health of UK exports.
Forecast Analysis: The "Actual vs. Forecast" analysis allows for a nuanced understanding of performance, showing where results have exceeded or fallen short of data-driven expectations.
Country Deep-Dive: The "Country Deep-Dive" page successfully identifies top contributing nations by value while also revealing which partners are demonstrating the strongest growth trends, providing a basis for strategic focus.

Technical Implementation Details

Python Data Processing:

Data transformation from wide to long format using Pandas
Missing value handling and data validation
Monthly aggregation for consistent time series analysis
Prophet model implementation for seasonal forecasting

Power BI Data Modeling:

Star schema design with FactExports as central table
Date dimension table for time intelligence functions
Country dimension table for geographic analysis
Optimized relationships for performance

DAX Measures Developed:

Month-over-Month Growth calculations
Year-over-Year Growth metrics
Rolling 12-Month Export totals
Forecast vs. Actual variance analysis

Dashboard Features

Performance Overview Dashboard

Key performance indicators and export trends visualization

Actual vs. Forecast Analysis

Comparison of actual performance against predictive forecasts

Country Deep-Dive Analysis

Geographic breakdown of export performance and growth trends

Interactive Features:

Drill-down capabilities for detailed country analysis
Time period filtering and selection
Cross-filtering between different visualizations
Export functionality for reports and presentations

Business Impact

Strategic Value:

Data-driven decision making for export strategy
Early identification of market trends and opportunities
Performance monitoring against predictive targets
Resource allocation optimization based on growth patterns

Operational Benefits:

Automated reporting reducing manual analysis time
Real-time performance tracking capabilities
Scalable solution for future data integration
User-friendly interface for non-technical stakeholders

Lessons Learned

Prophet's strength in handling seasonal patterns makes it ideal for trade data
Star schema design significantly improves Power BI performance
DAX measures require careful consideration of filter context
User feedback is crucial for dashboard design and functionality
Data quality and consistency are fundamental to accurate forecasting

Live Power BI Report

Interactive version of the UK Exports dashboard embedded below. Use the filters to explore the data. If the report does not load, ensure the publish settings allow public embedding or that you're signed in (for secure embeds).