Literature in Data Mining

Term Paper: Review of Related Literature in Data Mining Part B

Abstract

Data mining is useful as it enables the company to understand the existing data.

Big data analysis has required the development of sophisticated analysis tools, which are

valuable in the construction of sales forecast, for example. The project thus focuses on

the use of data mining techniques to forecast the future sales of a company. The estimates

of future sales are the first step that the company managers undertake to plan the

necessary resources and ensure that the company will be able to meet the demand.

Scope

The scope of the present project is to illustrate how data mining tools can serve

the company in the forecast of its future sales. Such sales forecast is crucial to, e.g.,

allocate the existing resources such that the products having the highest demand or the

highest profit get manufactured (Witten et al., 2016). From this point of view, the scope

of the present project is that of illustrating how data mining assists in the sales forecast

process.

Selection of the best approach

The best approach to the proposed analysis is to use data mining and forecasting

models to predict what future sales will be like. This approach compares different

methods, such as the simple moving average, the exponential smoothing, or the weighted

average models in an attempt to best predict the future demand for the company’s

products, thus demonstrating the utility of data mining processes in business

management.