Course
Case Study: Ecommerce Analysis in Power BI
СреднийУровень мастерства
Обновлено 06.2024Power BIData Visualization4 ч4 videos23 Exercises2,100 XP3,388Свидетельство о достижениях
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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.Предварительные требования
DAX Functions in Power BIData Visualization in Power BI1
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.
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.
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.
Case Study: Ecommerce Analysis in Power BI
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