Data Mining: A Solution for Business Problems

Running Head: DATA MINING 0
Data Mining
Report
Student name

Data Mining 1
Table of Contents
Abstract............................................................................................................................................1
Introduction......................................................................................................................................1
Background......................................................................................................................................1
Discussion........................................................................................................................................3
Conclusion.......................................................................................................................................4
References........................................................................................................................................5

Data Mining 2
Abstract
Data mining is useful for reporting and data analytics in different areas. Business is
process that requires much information for growth and benefits in term of profit from their
products and services ( Brown, 2012). Business models are providing helps to manage different
operations of organizations. In addition, they are requiring much information about the business.
This paper will provide a solution of a business problem through data mining approach.
Introduction
Data warehouse and Data mining are basic need of an organization. Prediction is
requiring for decision making of any process or new business. Data mining provides reports and
information about the business with the help of data warehouse. This paper will describe a
solution of a business problem through data mining approaches.
Background
Cross-Industry Process for Data Mining (CRISP-DM) is a methodology of data mining. It
is a process model, which is provides different steps for conducting data mining project. It is
break down the project in six stages, which is good for analytics process (Agarwal, 2018).
Source: (Abbas, 2005)