Implementation
1. Data Extraction and Preparation:
- Datasets were gathered from stakeholders and cleaned by removing duplicates, handling missing values, and standardizing data formats for consistency.
- Derived metrics such as gross margin and net margin were calculated, and data was prepared for further analysis.
2. ETL Process:
- Extract: Data was extracted from CSV sources and brought into a staging area for preprocessing.
- Transform: The data was cleaned, formatted, and transformed to meet the requirements of target data storage and analysis needs.
- Load: Transformed data was loaded into a cloud-based data warehouse (Azure) for further processing and analysis.
3. Data Analysis and Dashboard Development:
- SQL queries were used for initial data analysis to uncover insights from shipment and order transaction data.
- Power BI was utilized to create interactive dashboards that displayed key metrics such as shipment volumes, total sales, profit breakdowns, and tax analysis. These dashboards provided stakeholders with an intuitive way to navigate and interpret the data.
Results
The analysis provided several key insights, including:
- Shipment and Order Analysis: Patterns were identified in shipment volumes, delivery performance, and return order trends across different regions and payment methods.
- Financial Analysis: Key metrics such as gross margin, net margin, and GST breakdowns by product, state, and day were visualized, allowing stakeholders to better understand their financial performance.
- Sales and Profit Analysis: The dashboards highlighted total sales, profit distribution across products, and regional performance. This helped the business pinpoint which areas were contributing the most to revenue and profitability .
Client Feedback
