To use data analysis, especially time series, to help a business succeed by finding insights and predicting sales.
The data is SuperStore sales data from a company based in United States. It has order_date, product, category, quantity, price, profit, and Region etc. It covers two years, from 2019 to 2020.
- Clean and prepare the data: Check and fix missing values, outliers, duplicates, and data types.
- Explore the data: Use statistics, graphs, and tests to understand the data and its patterns.
- Analyze the time series: Use techniques like decomposition, stationarity, autocorrelation, and forecasting models to study the sales over time.
- Create a dashboard: Use a tool like Power BI to make an interactive dashboard to show the data and the analysis results.
The results are:
- Insights on the sales performance, seasonality, and growth of the company by product and category.
- Accurate sales forecasts for the next 15 days.
- An interactive dashboard that lets the user explore the data and the analysis results easily.
The project uses sales data from the following sources:
Please refer to the documentation for more details on the data schema and structure.
You can access the interactive dashboard on our website: https://app.powerbi.com/view?r=eyJrIjoiNWQwNmVjOWUtYjBlNi00Mzk3LTllYzAtZTlkYWIzMmM0NDUwIiwidCI6IjVlMjVjZTVhLWJlMzItNGUxYy05MjczLWYyY2MzODYzYjkzYSJ9
The conclusion is that data analysis, especially time series, can help a business to do better by giving insights and predicting sales. The project also shows the skills and knowledge of the data analyst in using these techniques and making a dashboard.