In this first chapter, you’ll build a data model for sales and expense analysis. You’ll combine multiple files, filter out invalid data, and create metrics for customers and orders. You will utilize Power Query to help determine products that are frequently purchased together.


Analyzing ecommerce data

Bringing in the data

Supply chain costs

Data clean up

New customer measures

Products and shipping

Looking at quantities

Market basket visualization

Data Exploration

Next, you’ll create metrics for the most profitable products and customers. You’ll build a map of sales by state, before exploring the shipping cost metrics. Finally, you’ll build a what-if analysis to display the impact of shipping higher quantities on shipping costs.

Ecommerce analytics

Add state-region mapping

Sales by state exercise

What-if analysis metrics: Part 1

What-if analysis metrics: Part 2

Shipping costs by product

What-if analysis

Ecommerce Analytics

In the final chapter, you’ll build multiple dashboard-style pages, in order to create a data story for your audience. You’ll display the product and customer KPIs and visuals. To round off, you’ll recommend specific actions to reduce shipping expenses.

Creating a cohesive story

Revenue and profits

Build an executive summary

Profit percentage treemap

Profit percentage exercise

Shipping costs dashboard

Final dashboards

Wrap-up

Visualize Your Analysis

DataCamp vs. Local Experience

Exercises and Datasets

Metadata sheet

In this Power BI case study, you’ll explore a real-world ecommerce business dataset to uncover insights for an online pet supply company called Whiskique. Using what you’ve learned from previous courses; you’ll use Power Query to investigate and clean the data to find out how the company’s sales are performing and where their customers are located. You’ll then use DAX to build insightful visualizations of your findings. Finally, you’ll bring it all together using everything Power BI has to offer to create dashboard-style pages so that you can answer questions for the Whiskique executive team.

For ecommerce businesses, increasing sales and reducing expenses are top priorities. In this Power BI case study, you'll investigate a dataset from a fictitious online pet supply company called Whiskique. <br><br> <h2>Use Your Power BI Skills to Solve Real-World Problems</h2> First, you’ll analyze the sales dataset to inform the company of who their customers are and what purchases they make. You will then use market basket analysis to help identify which products are frequently bought together. <br><br> Next, you’ll need to address the fact that shipping costs remain a big expense for online retailers. You’ll work on strategies such as shipping more of the same product to reduce per-unit costs.<br><br>
<h2>Analyze The Data and Visualize Your Findings</h2> As you collate your findings, you’ll create new measures and various visualizations in Power BI, such as combination graphs, treemaps, and maps. Finally, you'll use filters and parameters to make your graphs dynamic and create dashboard-style pages to share your insights.

DAX Functions in Power BI

Data Visualization in Power BI

In ecommerce, increasing sales and reducing expenses are top priorities. You'll investigate data from an online pet supply company using Power BI.

Case Study: Ecommerce Analysis in Power BI

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

What-if analysis metrics: Part 2

Case Study: Ecommerce Analysis in Power BI

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