National Rail Dashboard by Krzysztof Turko

National Rail Dashboard by Krzysztof Turko

About the Project

The "National Rail Dashboard" project was created as part of the Maven Rail Challenge. The goal of the project was to present a comprehensive analysis of data related to train ticket sales, train punctuality, and their delays and cancellations. Maven Analytics provided detailed data that included information on ticket purchase transactions, ticket types, payment methods, journey details, delays, cancellations, and reasons for these events.

Key Indicators

Number of Passengers (Passengers)

Number of Completed Train Trips (Train Trips Complete)

Percentage of Delayed Trains (Delayed)

Percentage of Cancelled Trains (Cancelled)

Total Ticket Sales Revenue (Revenue)

Reasons for Delays and Cancellations (Reason for Delay and Cancellation)

Report Structure

The report consists of three main sections that enable a comprehensive analysis of railway data.

Dashboard Overview

The main page presents key indicators in the form of cards, allowing for a quick understanding of the overall performance of the railway system. The cards display:

The number of passengers, considering those who requested refunds and subtracting them, along with a weekly trend (WoW) and the number of completed train trips.

The percentage of delayed trains and the related refund requests.

The percentage of cancelled trains and the related refund requests.

The total ticket sales revenue, considering deducted refund amounts, and the average ticket price.

The line chart below the cards shows peak travel hours by the number of passengers, enabling the analysis of traffic intensity throughout the day. By clicking on individual cards, the user can dynamically change the chart view to see delays, cancellations, and revenues at specific hours.

The matrix on the right side presents the most popular routes in terms of the number of passengers, the number of train trips, delays, cancellations, and revenues. By selecting a specific route, the user can navigate to a detailed analysis of that route.

Revenue Analysis Page

This section focuses on the analysis of revenues and financial losses. Key indicators at the top of the page present total revenue, the number of transactions, and the number of refund requests.

Revenue by Top 5 Popular Trips: A bar chart showing the five routes generating the highest revenues, allowing the identification of the most profitable connections.

Revenue by Date of Journey: A line chart illustrating ticket revenues over time, enabling the analysis of seasonal revenue trends.

Passengers by Date of Journey: A line chart that dynamically changes depending on the selected indicator (number of passengers, number of train trips, cancelled trains, delayed trains), allowing for correlation between revenues and other operational indicators.

Revenue by Ticket Type, Class, and Payment Method: Three pie charts presenting the analysis of revenues by ticket type, class, and payment method, helping to understand which segments generate the most revenue.

Trips Analysis Page

This page analyzes the punctuality and operational efficiency of train routes.

Reason for Cancelled & Delayed: A bar chart showing the main reasons for delays and cancellations, allowing the identification of the most common operational issues.

Cancelled & Delayed Trend by Month: A line chart showing the monthly trends of train delays and cancellations, helping to understand seasonal patterns.

Delayed Analysis: A heatmap presenting the analysis of delays at different hours of each day of the week, enabling the identification of delay patterns.

Pick Travel Time: A histogram showing peak travel hours by the number of passengers, crucial for effective traffic and resource management.

Analysis and Insights

As the author, I focused on identifying key patterns and operational issues in the railway data. For example, analyzing the reasons for delays and cancellations chart allows identifying the main causes of problems, such as signal failures and technical issues, which can help in taking corrective actions. The charts presenting peak travel hours and revenue trends help in better understanding seasonality and traffic intensity, which is crucial for resource planning.

Design

The dashboard design was inspired by the latest trends in data visualization, utilizing a blur effect in the background, giving it a modern and professional look. The background was created using Figma, allowing for an aesthetic and clear layout that facilitates data analysis.

This project provides a comprehensive tool for monitoring and analyzing railway operations, helping to identify key issues and opportunities to improve efficiency.