Predictive Analytics (with R)

Project Definition Define project outcome – predict next year sales for company. Scope – provide better understanding for future decision making. Business objective – extract profit and targets of next year’s sales. Identify data set – identify parameters affected by the sales.

Data Collection Collect company data from multiple sources for analysis to predict sales for coming year Collect most affected parameters like sales year, dealer code, dealer information, employee code, employee visit, sale amount, target of each sale, time spent on each visit etc.

Data Analysis Collection of useful information from different tables and cleansing of data like missing values, inappropriate data, formatting data, thereby extracting a useful data set for the prediction model.

Statistical Analysis Create a statistical model to predict the next year’s sale, with multiple linear regression algorithm. Validate the assumption, hypothesis and test it using standard statistical models.

Data Modeling Create accurate predictive model predicting the future sales amount of the company and yet another creating city wise prediction analysis. Validate the accuracy of these models through MLR validation techniques.

Deployment Deploy the analytical results of the model for company to easily visualize and identify next year’s company sales, through a predictive dashboard.