This Power BI project presents a comprehensive sales analysis and forecasting dashboard for Kraken Koffee — a fictional Florida-based coffee chain. The infographic-style report visualizes half-year (Jan–Jun 2023) performance across store locations, product categories, time of day, and transaction patterns. It also includes a full-year sales forecast powered by advanced DAX measures.
- Summarize sales activity across three store locations
- Identify top-selling products and peak revenue hours
- Analyze customer buying behavior based on time of day
- Forecast year-end sales using current performance trends
- Present findings in a visually engaging, single-page infographic layout
- Total Sales, Transactions, Average Order Size
- Best-selling and top-earning products
- Heatmap and trend charts for daily/monthly performance
- FY 2023 sales forecast per store and overall
- 56% of revenue is generated during morning hours
- Peak average order size at 8–10 AM
- Visual breakdown by hour and weekday
- Coffee and Tea lead sales by category
- Davy Jones' Organic Hot Chocolate (Large) is the top revenue earner
- Crow’s Nest Croissant is the most frequently purchased item
- Dynamic labeling and color highlights used to emphasize top performers
- Tampa store recorded the highest total sales (~$240K)
- Store-wise forecasting shown using clean line visuals with markers
- Comparative view of total and average order size per store
- Tampa store led all locations in revenue, generating over $240K in H1.
- Morning hours (6–11 AM) accounted for more than 56% of total sales, with peak order size observed around 8–10 AM.
- Davy Jones’ Organic Hot Chocolate (Large) was the top-earning product, while Crow’s Nest Croissant was the most frequently purchased.
- The FY 2023 sales forecast projects over $1.41M in total revenue, based on current daily trends.
- The infographic layout and dynamic DAX logic enable quick drilldowns by store, category, and time of day for deeper decision-making.
The report is powered by a clean star schema optimized for performance and clarity
- Kraken_Koffee_Fact :Fact table with transactional data: sales, time, store, product
- Store_Dim :Store metadata, location, ID
- Product_Dim :Product details, category, type, ID
- Date :Standard calendar dimension used for time intelligence
- Forecast Date Table :Custom date table supporting forecast visuals and line plots
This project relies heavily on DAX to drive dynamic logic, product ranking, visual formatting, and forecasting. Below is how each group of DAX measures adds value to the report:
Total Sales: Aggregates revenue from all transactions; central to most charts and cards.Total Transactions: Measures customer traffic; supports AOS (Average Order Size).Total Products&Total Stores: Used for counts in infographic headers and filters.Average Order Size: Indicates customer spend per transaction; used in hourly visuals and as a summary metric.Top Earner: Identifies the highest revenue-generating product dynamically.Most Popular Seller: Shows the most frequently purchased product by transaction count.
Product Sales Rank: Ranks products by revenue for sorting and label logic.Product Transaction Rank: Ranks products by number of transactions.Product Category Rank: Used for conditional formatting and top 10 highlighting.
% of Sales: Calculates share of total sales per category/product — used in labels and tooltips.Max Avg Order Size (Hour): Determines which hour had the highest average order size.Max AOS Marker: Used to place a marker only at the peak hour in time-based visuals.Bar Chart Label (Product Category): Combines dollar and percent formats for intuitive bar chart labeling.Top 10 Product Type Highlight: Applies dynamic color based on ranking — gold for top 10, blue otherwise.MAX AOS Marker Label: Creates a labeled data card for the peak AOS hour.
Average Daily Sales: Calculates base daily average sales.Average Daily Sales 2: Respects visual filters to produce consistent outputs.Average Daily Sales Switch: Smart logic to fallback on average where data is missing.Forecast: Main measure used to estimate FY 2023 sales based on trends.Forecast Label: Displays final projected sales cleanly on KPI cards.Forecast Marker: Used to highlight December data point in forecast line visuals.
- Retail chains rely heavily on time-based and product-level insights to optimize inventory, staffing, and promotions. This dashboard:
- Provides time series forecasting to anticipate full-year sales performance
- Identifies high-performing products and hours to inform marketing and store operations
- Enables store comparisons and product mix analysis at a glance
- Demonstrates strong data modeling, DAX, and Power BI storytelling skills, suitable for business reporting and executive decision support
This Power BI report empowers business users with dynamic sales insights, time-based performance views, and a full-year forecast — all presented through a clean, infographic-style layout. DAX plays a central role in making the report highly interactive and intelligent, from label formatting to visual rankings and future sales projection.