Develop a real-time data analytics dashboard that monitors retail sales performance, customer trends, and inventory movement. The system will help businesses make data-driven decisions by visualizing key performance indicators and generating actionable insights from transactional datasets.
Study retail sales data structures and identify KPIs such as revenue, profit margin, and conversion rate.
Design a relational database schema to store sales transactions and product details.
Implement ETL processes to clean and transform raw sales data.
Develop backend modules using Python/SQL for data aggregation and analytics.
Create interactive dashboards using Power BI/Tableau.
Implement filters for region, product category, and time period.
Apply statistical techniques to identify sales trends and seasonality.
Integrate forecasting models to predict future sales performance.
Test dashboard usability and optimize performance for large datasets.
Document insights and prepare analytical reports.
