Data Warehousing and Data Mining

Data Warehousing and Data Mining

Introduction

We live in the age of information. Data is the most valuable resource of an enterprise. In today's competitive global business environment, understanding and managing enterprise wide information is crucial for making timely decisions and responding to changing business conditions. Many companies are realizing a business advantage by leveraging one of their key assets - business Data. There is a tremendous amount of data generated by day-to-day business operational applications. In addition there is valuable data available from external sources such as market research organizations, independent surveys and quality testing labs. Studies indicate that the amount of data in a given organization doubles every 5 years.

Data warehousing has emerged as an increasingly popular and powerful concept of applying information technology to turn these huge islands of data into meaningful information for better business. Data mining, the extraction of hidden predictive information from large databases is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions.

Benefits and Current Trends of Data Warehousing and Data Mining

Data mining is not an “intelligence” tool or framework, typically drawn from an enterprise data warehouse is used to analyze and uncover information about past performance on an aggregate level. Data warehousing and business intelligence provide a method for users to anticipate future trends from analyzing past patterns in organizational data. Data mining is more intuitive, allowing for increased insight beyond data warehousing. An implementation of data mining in an organization will serve as a guide to uncover inherent trends and tendencies in historical information, as well as allow for statistical predictions, groupings and Classification of data. (Linstedt, 2010)

Dramatic advances in data capture, processing power, data transmission, and storage capabilities are enabling organizations to integrate their various databases into data warehouses. Data warehousing is defined as a process of centralized data management and retrieval. Data warehousing, like data mining, is a relatively new term although the concept itself has been around for years. Data warehousing represents an ideal vision of maintaining a central repository of all organizational data. Centralization of data is needed to maximize user access and analysis. Dramatic technological advances are making this vision a reality for many companies. And, equally dramatic advances in data analysis software are allowing users to access this data freely. The data analysis software is what supports data mining.

Company Examples

Data Warehouses and Data Mining techniques are becoming indispensable parts of business intelligence programs. Use these links to learn more about these emerging fields and keep on top of this trend. Following are the 2 examples of the companies that are using data warehousing and data mining.

1. The data mining technologies from IBM help you to detect fraud, prevent customer churn, segment your customers, and simplify market basket analysis. The in-database data mining capabilities integrate with existing systems to provide scalable, high performing predictive and pattern analysis without moving ...