README
Open on GitHub ↗Global-Superstore-Sales-Dashboard-Using-Power-Bi
The interactive dashboard is designed to be used by retailers and provide them with a high-level to granular understanding of how different products perform. It provides an overview of total sales, with the ability to showcase yearly, quarterly, and monthly growth rates.
Objective
To contribute to the success of a business by utilizing data analysis techniques, specifically focusing on time series analysis, to provide valuable insights and accurate sales forecasting.
Process
To help supermarkets achieve their goals for growth, efficiency, and customer satisfaction, I can assist in several ways.
I can help identify key performance indicators (KPIs) and design an intuitive and visually appealing dashboard. This dashboard can include interactive visualizations and filtering capabilities, allowing users to explore data at different levels of detail.
I can provide valuable insights to businesses about the effectiveness of their sales strategies through charts and visualizations. This will help them make informed decisions about how to improve their sales performance.
I can leverage historic data and apply time series analysis to generate sales forecasts for the next 6 months. This will provide businesses with a better understanding of future sales trends, allowing them to plan and prepare accordingly.
Overall, my ultimate goal is to provide useful insights and actionable information that can support strategic decision-making and help businesses achieve their objectives.
Interactive Dashboard
Sales Forecasting for the next 6 months
Forecasting is an important tool that helps businesses plan and make informed decisions about their future sales strategies and resource allocation. One way to do this is by predicting the sales and revenue of a superstore using historical data from 2019 and 2020.
Project Insights
- The sales total for this period was 2 million, resulting in a profit of 175k. Unfortunately, there were 5901 product returns.
- The profit was divided by category and segment, with the technology category being the most profitable and the corporate segment generating the most profit.
- Based on our analysis of profit across different regions, it appears that the western region is the most profitable. However, it's important to note that profitability can vary based on a
number of factors and it's always important to consider the specific circumstances in each case.
Conclusion
We have utilized Power BI to analyze the sales data of our superstore and have gathered valuable insights that can significantly benefit business owners and decision-makers. Through this analysis, we have identified customer behavior, identified our top-performing products, and developed accurate sales forecasts. By utilizing this information, businesses can optimize their operations and effectively drive growth. I am thrilled to incorporate these insights into our future endeavors and believe they will elevate our business to new heights.