Abstract
This paper considers key factors regarding data warehousing. It looks at the goal of data warehousing and the differences of data warehousing and relational databases.

From the Paper
"Data warehousing is particularly popular in environments which have complex data requirements and a broad spectrum of data types contained in its database. The goal of data warehousing is to take full advantage of the power of hardware to contain large quantities of data and use the databases to manipulate that data. Although not yet implemented across all computing environments data warehousing is becoming popular as hardware becomes more powerful and cost effective..."

Tags:distributed data warehousing systems, data warehouses

Abstract
This paper explains the general concept of data warehousing . The paper explores the use of data warehousing at Humana, Inc., a giant healthcare company. The paper explains the strengths and weaknesses of data warehousing at Humana.

From the Paper
"Humana Incorporated is a healthcare company with ... billion in revenue and stakeholders that include medical professionals, employees, corporate clients and other agents. Until early ..., the company had separate databases for various parts of its business making it difficult to understand the large amounts of data that was being generated by the organization and even making it difficult for healthcare providers to have access to all appropriate information on occasion. As a result, the company developed a data warehouse that uses two discrete data ..."

Tags:Humana, data warehousing

Abstract
The report starts with the basics of data warehousing and later gives an overview of the framework that should be followed by management for optimum utilization of resources in data warehousing.

Tags:data, warehousing

Abstract
This paper explores data warehousing in terms of data mining with intelligent agents such as bots and ants and clarifies the ethical dilemma posed by the use of such data.

From the Paper
" Data warehousing is no longer simply a storage system for data. Today's data warehousing involves innovative technological software, automated agents known as intelligent agents robots-or bots and ants. These agents ..."

Tags:data warehousing, data mining, intelligent agents, robots, bots, ants, personalization, ethics

Abstract
This paper describes, studies and analyzes the different aspects and importance of implementing data warehousing in organizations.

Tags:analysis, data, warehousing

Abstract
Many authors have provided an enormous amount of literature on data warehousing concepts, processes, and characteristics. However, the key to a successful data warehouse is proper implementation. Previous publications have come up with different ideas and methods to implement a data warehouse successfully. Managers don?t have enough time to go through all these readings This paper provides an integration of the various implementation guidelines with practical examples ranging from the FBI to Wal-Mart.

I. Introduction
II. Basic Definitions and Concepts of Data Warehousing
III. Brief History of Data Warehousing
IV. Data Warehousing Characteristics
V. Drivers of Data Warehousing
VI. Data Warehousing Process
VII. Current Issues and Practices of Data Warehousing
VIII. Guidelines in Implementing a Data Warehouse
IX. Conclusions, Limitations, and Future Research Guidelines
X. References

From the Paper
"Data warehousing is one of the hottest developments of the 1990s. In 1998, the expenditure on data warehousing was $14 600 million (META Group 1996). It is estimated that 95% of the Fortune 1000 either have a data warehouse or are planning to develop one (META Group 1996). A data warehouse may help increase a company's sales by supporting decision-making and understanding consumer behavior. For example, Office Depot sales increased by $117 million after investing on data warehousing (Anthes 2003)."

Tags:warehousing, fbi, walmart

Abstract
These paper presents the overall aims and objectives of a research proposal on data warehousing. The paper then provides information that documents the state of the art in research focused on data warehousing within organizations, as well as a justification for further research in this area. Finally, the research methodology to be employed, the deliverables associated with the research, and a work plan are delineated.

From the Paper
"As noted by Foote and Krishnamurthi, (2001), until very recently, the forecasting process used by companies was relatively subjective and was dependent upon the opinions of company executives, sales force analysts, and industry analysts, who were not always extremely reliant in aiding the company to in the production of satisfactory outcomes. Quite frequently, as reported by Foote and Krishnamurthi, companies found that they had missed the mark in forecasting and consequently had failed in achieving profitability, reliability and a competitive vantage position in their industry. Thus, companies are increasingly recognizing the value of investing in an information system to support their forecasting process. According to Foote and Krishnamurthi, a data warehouse has come to be identified as assuming a pivotal role in gaining the knowledge needed by companies to implement reliable systems for forecasting."

Tags:competetive, advantage, integrated, forecasting, process, information, system, extraction, cleaning, transformation, loaded

Abstract
This paper explains that one of the major challenges in any data-warehousing project is the proficient amalgamation of large volumes of information of data available for analysis, which must include the customer database, the supplier database and the distributor database, all well integrated into the data-warehousing project. The author points out that data warehousing is an expensive undertaking especially because the beer industry depends extensively on distributors and suppliers and must maintain data on their extensive logistic and distributing channels. The paper stresses that knowledge acquisition is the first step for gaining advantages in the market place; therefore, data warehousing should facilitate internal research to identify new ways of doing tasks within the organization and systematic problem solving efforts. Illustrations.

Table of Contents
Introduction
Objective
Problem Statement
Hypothesis
Methodology
Sampling Procedures
Sources of Data
Literature Review of Data Warehousing
Discussion
Recommendations
Conclusion

From the Paper
"Interviews will also be conducted with an additional 50 companies to identify the applications, if any, of data warehousing and the impact that this concept has made on the organization as a whole. This interview will be based on a fixed set of questions. All of the questions will be discussed with every individual. Interviews, in addition to data collection relevant to the question asked, can also identify the non-verbal reactions to the questions asked. Non-verbal communication could be in the form of the comfort level that the interviewee displays, the hand and eye movements and the facial expressions that might be made. The success of data collection using the interview methods is also dependent on the skill and personality of the interviewer. An interviewer who is able to introduce a level of comfort and camaraderie in the interviewee may be able to get more realistic and correct answers. Questions used in the study can be open-ended, where the subject is free to answer the question and discuss relevant issues that might be relevant to the question."

Tags:correlation, interviews, amalgamation, information, channels

Abstract
The paper examines how manufacturing companies are relying on data warehousing for more effective new product development and introduction (NPDI) processes, workflows and strategies. The paper focuses on data warehousing's contributions to value chain performance and customer relationship management strategies. The paper clearly demonstrates how data warehousing is now a competitive weapon used at the strategic level of companies looking to gain greater efficiencies from every area of their value chains. The paper includes two diagrams.

Outline:
Introduction
Data Warehousing's Contributions to Value Chain Performance
Creating Competitive Advantage Using Data Warehousing in Customer Relationship Management Strategies
Conclusion

From the Paper
"The strategic framework of the value chain (Porter, 1986, 9) provides a frame of reference for illustrating how data warehousing is making strategic contributions across entire enterprises. The increased accuracy and velocity of information made possible through integrated data warehousing strategies has the potential to significantly redefine entire companies (Johnson, 2009, 9). As the value chain framework as defined by Porter (1986, 9) compares the functional areas of Inbound Logistics, Operations, Outbound Logistics, Marketing & Sales and Aftersales Service while also showing support activities, this framework illustrates just how critical interprocess and system integration is in any value chain strategy."

Tags:Continental, Airlines, Wal-Mart, Porter, value, chain

Abstract
This paper analyzes the interrelated topics of data warehousing and datamining. The author begins by defining the terms, then giving a brief overview of how and why the two concepts emerged. The author then discusses some of the issues involved when implementing a data warehousing/datamining application. Then, the author launches into a description of datamining and why it is an essential aspect of data warehousing. After a discussion of why an implementation is difficult and why man fail, the author then assesses how the two concepts may be of interest to those in the food service industries. The author closes the piece by discussing the case of Pizzeria Uno, a casual dining franchise which became more profitable from data warehousing and datamining.