Analyzed the sales of a store over two years, and made significant conclusions from the data(data_analysis). Further forecasted what could be the sales in the coming 15 days(sales_forecasting).
- User Friendly
- Interactive Dashboard section for the data analysis and insights.
- Microsoft PowerBI
- Microsoft Excel
Data analysis and sales forecasting are crucial components of business planning and decision-making. They involve analyzing historical data and using it to predict future sales trends
- Data Analysis: Data analysis involves examining raw data to discover meaningful insights, patterns, and trends. In the context of your project, data analysis might involve.
- Data Collection: Data Collection: Gathering relevant data sources, such as sales transactions, customer information, marketing campaigns, and external factors like economic indicators or seasonality.
- Data Cleaning and Preparation: Ensuring the data is accurate, complete, and ready for analysis by addressing missing values, inconsistencies, and errors.
- Statistical Analysis: Applying various statistical methods to identify correlations, relationships, and potential causality between different variables.
Sales forecasting is the process of estimating future sales volumes and revenue based on historical data and other relevant factors. It helps businesses make informed decisions about production, inventory, staffing, and marketing strategies.
- Time Series Analysis: This method involves analyzing historical sales data over a period of time to identify patterns, seasonality, and trends. Techniques like moving averages, exponential smoothing, and ARIMA (AutoRegressive Integrated Moving Average) models can be applied.
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