Let’s take a step by step approach to start a Sales Forecasting project. In this project, we aim to forecast future sales using past sales data. Sales forecasts are of great importance in critical decisions of businesses such as inventory management, production planning, and budget estimation.
Project Plan
Purpose of the Project:
Forecasting future sales based on historical sales data.
Creating forecasting models using methods such as time series analysis and regression.
Analyze forecast results and make strategic recommendations for the business.
Dataset:
TransactionID: The unique ID of each sales transaction.
SalesDate: The date the sale occurred.
ProductID: Unique ID for each product.
ProductCategory: The category to which the product belongs.
Quantity: The amount of product sold.
Price: Unit price of the product.
TotalSalesAmount: The total amount of the sale.
Steps:
Data Loading and Preparation:
The dataset will be loaded and data cleaning operations will be performed.
Time Series Analysis:
We will examine sales data as a time series and try to determine trends and seasonality.
Creating a Forecast Model:
By creating time series forecasting models (ARIMA, Prophet) and regression model, we will predict future sales.
Model Evaluation:
By measuring the accuracy of the prediction models, we will select the best performing model.
Reporting Results:
We will report the forecast results and make recommendations for the business.
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