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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.

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3 Hours4 Videos23 Exercises

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Course Description

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.

Use Your Power BI Skills to Solve Real-World Problems

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.

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.

Analyze The Data and Visualize Your Findings

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.
  1. 1

    Data Exploration


    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.

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    Analyzing ecommerce data
    50 xp
    Bringing in the data
    100 xp
    Supply chain costs
    100 xp
    Data clean up
    100 xp
    New customer measures
    100 xp
    Products and shipping
    100 xp
    Looking at quantities
    100 xp
    Market basket visualization
    100 xp
  2. 2

    Ecommerce Analytics

    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.

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  3. 3

    Visualize Your Analysis

    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.

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DataCamp vs. Local ExperienceExercises and DatasetsMetadata sheet


Collaborator's avatar
Jess Ahmet
Iason Prassides HeadshotIason Prassides

Content Developer at DataCamp

Iason holds a Master’s degree in Chemistry from UCL and is now a Content Developer at DataCamp. He is also a certified Power BI data analyst. Prior to working at DataCamp, Iason held a number of analytics roles within a range of industries across different countries. Having a passion for education, data, and storytelling, he has found a great place at DataCamp to develop engaging content for learning. As an avid sports fan, he has a keen interest in sports statistics
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