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Adventure Works is a bike manufacturer and seller and in this project I analyze their sales and returns data using Microsoft Power BI Desktop.

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Overview Adventure Works, a renowned bike manufacturer and seller, provided their sales and returns data for analysis. This end-to-end project involved data importing, cleaning, modeling, and visualization using Microsoft Power BI Desktop.

Data Cleaning The raw dataset, provided in .csv format, was imported directly into Power BI. A total of 8 files were imported, each representing a distinct table. The primary focus was on Sales and Returns data. The cleaning process included:

Ensuring columns were appropriately titled. Correcting data types. Checking for missing data (none was found). Identifying potential relationships between tables.

Data Modeling After verifying data accuracy and consistency, a data model was created: Established primary tables: 'Sales Data' and 'Returns Data'. Defined relationships, primarily one-to-many. The completed model is illustrated below for better understanding.

DAX Functions With table relationships in place, DAX functions were utilized to analyze the dataset. Key DAX functions used include:

ITERATOR FUNCTIONS (SUMX): Evaluates an expression for each row and aggregates results. CALCULATE(): Overrides filters to create new filter contexts, useful for metrics like Previous Month's Orders, Revenue, Profit, Returns, and Overall Average Price. RELATED(): Pulls data from different tables with established relationships. Date Functions (DateAdd, DATESINPERIOD): Essential for calculating metrics like 90-Day Rolling Profit and monthly comparisons. Measures created for this project were organized into a dedicated Measure Table.

Data Visualization The report includes four visualization pages:

• Executive Dashboard: Key performance indicators and summary metrics. • Map: Geographical representation of sales data. • Product: Detailed analysis of product performance. • Customer Detail: Insights into customer behavior and demographics. Each visualization page offers a unique perspective, enabling comprehensive data analysis and informed decision-making.

Conclusion This project demonstrates a thorough process of data cleaning, modeling, and visualization using Power BI, providing valuable insights into Adventure Works' sales and returns. The use of DAX functions and clear visualizations ensures a robust analysis, aiding in strategic planning and operational efficiency.

For more details, check out the full Power BI report.

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Adventure Works is a bike manufacturer and seller and in this project I analyze their sales and returns data using Microsoft Power BI Desktop.

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