Project Overview & Usage Guide

This is the home page for the dashboard. To view the full analysis, click on "E-commerce Dashboard" from the menu on the left.

💡 Tip: Before diving in, check out the "How to Use This Dashboard" section below to learn how to view the underlying SQL queries and get the most out of the interface.

Business Context/Scenario

This dashboard was created for the Analytics team at a Brazilian e-commerce marketplace to help the Operations and Growth teams monitor performance, understand customer behavior, and guide decision-making around marketing, logistics, and promotions.

Key business questions this dashboard helps answer:

How are revenue and orders trending over time?
What’s the average order value and how does it shift?
Which product categories drive the most sales volume?
How do customers prefer to pay, and are promos overused?
Where are our highest-value customers located?
Which sellers are generating the most revenue and volume?
Which regions have the highest customer concentration?

This dashboard uses realistic e-commerce transaction data (simulated) and is designed to be used by:

The Operations team (delivery times, region analysis)
The Growth & Marketing team (category performance, AOV)
The Finance team (payment method breakdown)

It supports custom date ranges and is meant to be reviewed on a weekly or monthly basis.

How to Use This Dashboard

To hide/show SQL queries click the "…" menu on the top right and click either "Show Queries" or "Hide Queries" (They will not appear on this page, but on the E-Commerce Dashboard" page)
You can then click on the individual query name or records to see either the query or the query results respectively
You can also toggle Light/Dark mode from the "…" menu as well
Adjust the Date Range at the top of the dashboard to filter all metrics and visualizations dynamically
You can navigate the page by scrolling, or you can click the individual sections at the top right under "On this page"
Use Alerts and Info Boxes throughout the dashboard to interpret key insights and business implications.

ℹ️ All SQL queries used in this project are also available at https://github.com/pbello22/E-CommerceProjectSQL/blob/main/queries.sql.

SQL Queries

All data visualizations and metrics are powered by SQL queries written in BigQuery SQL syntax. Each query is:

Fully parameterized using ${inputs.date_filter.start} and ${inputs.date_filter.end} for dynamic filtering
Designed for performance and clarity (using joins, aggregations, and window functions)

Tech Stack

Evidence.dev: Open-source BI tool used for building markdown-powered dashboards with SQL + modern components
BigQuery: Used for storing and querying data