Business Intelligence Portfolio

BI Dashboards &
Data Storytelling

Interactive Power BI dashboards that transform complex datasets into clear, executive-ready insights. Each project showcases data modelling, DAX calculations, and compelling visual narratives.

Stack: 📊 Power BI 🗃 SQL 📐 DAX 📋 Data Modelling
2
BI Projects
7
Dashboard Pages
22.2K+
Customers Analysed
$57.5M+
Revenue Tracked

Project 01 — Retail Analytics

Maven Market

Power BI Dashboard · 3-Page Report · Multi-Region Retail Data

● Completed

📋 Project Overview

Maven Market is a multi-national grocery chain operating across USA, Canada, and Mexico. This Power BI report delivers a comprehensive three-page business intelligence solution covering retail transactions, product performance, and customer analytics.

Built during the Microsoft Power BI Desktop for Business Intelligence course on Udemy, applying real-world data modelling techniques to a realistic retail dataset.

  • Data Sources: Transactions, Products, Customers, Stores, Calendar tables
  • Data Model: Star schema with dimension and fact tables
  • Measures: DAX calculated columns and KPI measures
  • Visuals: Map, treemap, bar charts, gauge, scatter plot, donut chart
  • Interactivity: Slicers, cross-filtering, drill-through

📈 Key Performance Indicators

269.7K
Total Transactions
$1.1M
Total Profit
59.67%
Profit Margin
7.1K
Total Returns
111
Distinct Brands
10.3K
Total Customers
$1.76M
Total Revenue
81.1
Avg Customer Age

📁 Dashboard Pages

Executive Overview page
Page 01
Executive Overview

KPI cards, product brand table with profit margin, map, regional treemap, monthly revenue bar chart, and revenue vs target gauge.

Product Detail page
Page 02
Product Detail

Top 10 brands by revenue, price tier donut chart (Low/Mid/High), product table, recyclable bar chart, and retail vs cost scatter plot.

Customer Analytics page
Page 03
Customer Analytics

Age band histogram, priority split pie chart, customer information table, and global distribution map by city.

Data Insights

Key Findings from Maven Market Analysis

🏆

Top Brand Performance

Hermanos leads with 8,071 transactions and $33,167 profit at a 58.54% margin, slightly above the 59.93% fleet average.

🗺

Regional Dominance

USA drives 180.8K transactions. Mexico contributes 72.8K while Canada fills the remaining volume across three countries.

📊

Revenue Seasonality

November peaks at $0.19M monthly while February dips to $0.12M — clear seasonality for targeted promotional planning.

👤

Customer Demographics

91.37% are Standard priority customers. Average age is 81.1 with peak concentration in the 60–80 age band.

🏷

Price Tier Mix

67.6% of products are Low tier; 15.5% Mid and 16.9% High — a value-focused assortment strategy across the range.

♻

Sustainability Score

544 recyclable vs 424 non-recyclable products — Maven Market maintains a 56.2% recyclability rate across SKUs.

Project 02 — Global Retail Analytics

Global Electronics Retailer

Power BI Dashboard · 9-Country Sales Data · Multi-Currency Star Schema

● Completed

📋 Project Overview

Global Electronics Retailer is a multinational consumer-electronics chain with 67 physical stores across 8 countries plus an online channel, selling everything from audio and cameras to computers and home appliances. This Power BI report models five years of transactional data (Jan 2016 – Feb 2021) into a multi-currency sales analysis covering revenue, channel mix, category performance, and brand contribution.

Built from five raw source tables — Sales, Products, Stores, Customers, and a daily Exchange Rates table — cleaned and modelled into a star schema to normalize CAD, GBP, EUR, and AUD transactions back to USD for consistent cross-market reporting.

  • Data Sources: Sales, Products, Stores, Customers, Exchange Rates tables
  • Data Model: Star schema — Sales fact table linked to 4 dimension tables
  • Data Cleaning: Currency-formatted price fields, encoding fixes, undelivered-order flagging
  • Measures: DAX measures for revenue, profit margin, and channel split
  • Visuals: Country bar chart, revenue trend line, category donut, brand ranking

📈 Key Performance Indicators

$55.8M
Total Revenue
$32.7M
Total Profit
58.6%
Profit Margin
26.3K
Total Orders
11.9K
Purchasing Customers
$4,690
Revenue per Customer
61.2%
Repeat Customer Rate
20.45%
Online Revenue Share

📁 Dashboard Pages

Global Electronics Retailer Overview dashboard page
Page 01
Overview

KPI cards for revenue, profit, margin, and orders, plus monthly revenue vs. last year, revenue by category, and in-store vs online revenue by year.

Global Electronics Retailer Product Analysis dashboard page
Page 02
Product Analysis

Top 5 brands by revenue, a margin-vs-revenue scatter chart by category, and a full category breakdown of profit, margin, units, and channel split.

Global Electronics Retailer Geography and Store dashboard page
Page 03
Geography & Store

Revenue by customer country on a Bing map and bar chart, an online vs in-store donut, and store performance ranked by revenue per square meter.

Global Electronics Retailer Customer dashboard page
Page 04
Customer

Customer KPIs, revenue by gender and age group, a top-10 customers table, and customer distribution by country.

Data Insights

Key Findings from Global Electronics Retailer Analysis

🏆

Market Leadership

The United States accounts for 5.7K of 11.9K purchasing customers — more than triple the United Kingdom, its closest market at 1.6K.

🌐

Omnichannel Reach

The Online channel contributes $11.4M (20.45%) of revenue against $44.35M generated across 67 physical stores.

💻

Category Concentration

Computers drive ~35% of revenue ($19M) at a 58.4% margin, while Music, Movies & Audio Books post the highest margin of all categories at 61.0%.

📈

Growth & Decline

Revenue climbed from $6.9M in 2016 to a peak of $18.3M in 2019, then fell through 2020 into a partial 2021.

👤

Customer Value & Loyalty

Customers generate $4,690 in revenue on average with a 61.2% repeat-purchase rate, and the 65+ age group is the single highest-revenue segment at $18.1M.

🏢

Store Efficiency

Wyoming (US) is the most efficient store at $1,454 revenue per square meter, ahead of Alaska ($1,051) and Hawaii ($1,010).

Under the Hood

Techniques & Methods Applied

The technical Power BI and data modelling skills demonstrated in this project.

Star Schema Data Model

Connected Transactions fact table to multiple dimension tables with proper one-to-many relationships.

DAX Calculated Columns

Created Profit Margin %, Price Tier classification, and Age Band grouping using DAX expressions.

DAX Measures

Built dynamic KPI measures: Total Revenue, Total Profit, Return Rate, and Revenue vs Target.

Bing Map Visualization

Geo-spatial plotting of store locations and customer distribution across North America and globally.

Conditional Formatting

Color-coded Return Rate column — green for low rates, red for high — enabling instant pattern recognition.

Slicer Interactivity

Region and Member Card slicers enabling dynamic cross-filtering across all visuals on each page.

Calendar / Date Table

Custom date table built with CALENDARAUTO() for accurate time intelligence and monthly aggregation.

Treemap & Scatter Plot

Treemap for regional distribution; scatter plot showing Retail Price vs Product Cost correlation.

KPI Gauge Visualization

Revenue gauge showing $1.76M achieved vs $3.53M target, providing immediate performance context.

Multi-Currency Exchange Table

Built a daily exchange-rate dimension to normalize CAD, GBP, EUR, and AUD transactions back to USD.

Multi-Country Star Schema

Modelled a 67-store, 9-country sales footprint with Sales as the fact table linked to 4 dimension tables.

Channel Segmentation

Isolated e-commerce performance from physical stores by classifying transactions by StoreKey.

Data Cleaning at Scale

Resolved currency-formatted price fields, encoding issues, and flagged ~79% of orders missing a delivery date.

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