| Papers [1-15] of 100 :: [Page 1 of 7] | | Go to page : 1 2 3 4 5 6 7 —> | Search results on "PANDATA DATA SERVICES": |
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PanData-A Data Services, 2005.
An analysis of a new company in the data warehousing/data services industry.
3,600 words (approx. 14.4 pages), 11 sources, $ 142.95
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Abstract
This paper discusses the realities of a new company in the data warehousing/data services industry and the exigencies of thriving in this field. The types of database products, services and supporting infrastructure are discussed as well as business processes and market requirements. The corporation as a business entity is also discussed in terms of its use and implementation of current and emerging technologies, change management techniques and the Internet as a tool and device.
From the Paper
"PanData is a data intelligence business concentrating on the data services industry: warehousing, intelligence, customer relations management (CRM) and list generation. PanData amasses data on the Retail & Foodservice Industries across the North American continent. It has over 70k unique companies in its database. The collected data consists of the following data elements: company contact information, personnel--CEO to mid-level management & buyers, trade areas, products, franchise information, parent companies, locations--geo-codes and addresses, market share information, technology related information--POS hardware/software, scanners, software systems, servers (corporate and in-store), databases/data warehouses, communications and connectivity, EDI, RFID, and Wifi. The types of data are considerable and this list is not all-inclusive. PanData envisions revenue in excess of 10m annually and this revenue is PanData's long-term goal. "
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Data Mining, 2005.
The paper is about data mining, which is the process of finding trends and patterns in data, often within a database.
3,546 words (approx. 14.2 pages), 10 sources, MLA, $ 99.95
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Abstract
Data mining has become a very important concept today and is used by companies all over the world to increase their profits and target the right market. The paper talks about the different aspects of data mining, tools used, and future trends in data mining. Data mining benefits are discussed in detail, and an entire discussion related to the trends in data mining is presented.
1-Background
2-Introduction
3-Data Mining Growth and Tools
4-The Data Mining Process
5-Data Mining Market Place Trends
6-The Data in Data Mining and Meta Data
7-Types of Data Mining Problems
8-Privacy and Ethical Sensitivity in Data Mining Results
9-Future Prospects of Data Mining
10-Works Cited
From the Paper
"Data, particularly in the vast diversity and immense quantity that it is available to modern business, was till recently almost very hard to find and understand. Yet, the comprehension of data is the most crucial step to extracting the knowledge that it contains. The scenario has drastically changed today where data is much more easily available and has become more "meaningful" with the utilization of Data Mining. Today, technology offers business managers powerful new tools for gleaning knowledge from data-the essentials of data mining. Data mining has become increasingly important to mainstream companies to become more competitive both in their workings and their customer based relationships. Data mining, as such is of great interest because it is imperative for organizations to grasp the competitive value of information contained within their data repositories. There are a number of pertinent benefits of data mining. First of all, data mining provides the tools and techniques that are essential for optimization of customer relationships. Secondly, data mining provides an automatic method of discovering patterns in data. Thirdly, but not the least, data mining tools can identify the relationships that are actually present in historical data."
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Data Warehouses, 2006.
An overview of data warehouses, one of the most powerful tools to impact the world of data management.
1,732 words (approx. 6.9 pages), 12 sources, APA, $ 55.95
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Abstract
This paper discusses the "architecture" of data warehouses and briefly describes possible future developments in data warehouses as well as restrictions in data warehouse technology.
Table of Contents
Introduction
Data Warehousing: Brief History
Data Warehouse Architecture
Restrictions
The Present and the Future
Conclusions
From the Paper
"There is little question that many critical enterprises in the world of today are dependent on quick and dependable access to information. From the halls of academia, to the world of business-science to medicine-the ability to readily access critical information within any particular organization or working entity is essential to survival and growth. However, even in today's technology-driven industries, it is often difficult for companies and other organizations to effectively provide the most comprehensive and critical internal information to those who need it."
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Data Warehousing Implementation, 2003.
An analysis of previous literatures on data warehousing implementation issues and guidelines for managers.
4,143 words (approx. 16.6 pages), 37 sources, MLA, $ 111.95
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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)."
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Data Warehousing, 2005.
This paper is a proposed study of data warehousing (DW) to improve decision-making process for a beer manufacturing and distribution company.
4,370 words (approx. 17.5 pages), 26 sources, APA, $ 115.95
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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."
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Data Warehousing: A Strategic Weapon of an Organization, 2004.
A study proposal to further explore the degree to which data warehousing has been effective in assisting companies with the process and activities of forecasting, as well as in gaining competitive advantage.
10,000 words (approx. 40.0 pages), 20 sources, APA, $ 202.95
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Abstract
This paper presents a study that aims to further establish the degree to which data warehousing has been used by organizations in achieving greater competitive advantage within the industries and markets in which they operate. In chapter One of this paper, an introduction of the study is provided, with the overall aims and objectives of the research proposal discussed. Chapter Two involves literature review on the subject. Chapter Three explains the research methodology, and Chapter Four uses this proposal on four case studies. Finally, Chapter Five provides a discussion and a review of the results.
Table of Contents
Introduction
Aims of the Study
Objectives of the Study
Significance of and Justification for the Study
Literature Review
Data Warehousing: Background
Deployment Obstacles
Data Warehouse Design
Benefits and Disadvantages Associated with Data Warehousing
Conclusions
Research Methodology
Research Design
Data Collection
Data Analysis
Results of the Study
Case Study One: Godrej Consumer Products Limited
Case Study Two: Safeway
Case Study Three: Wachovia Corporation
Case Study Four: Standard Chartered Bank
Discussion
Review of the Results
References
From the Paper
"Three of the companies were in periods of ongoing growth in relation to the evolution of data warehousing and its use within the companies while one company was still in the initiation-early deployment phase. While it would appear that some were in the maturity stage, most had specific plans for using the data warehouse as the basis for launching new business activities and strategies. On the basis of this evidence, it is particularly important to note that even during the initiation phase, it was possible for companies to begin to recognize gains in competitive advantage, which further supports the potential for data warehousing to aid businesses in gaining competitive ground."
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Data and Text Mining, 2007.
A discussion on how data and text mining tools are revitalizing the librarian profession.
4,555 words (approx. 18.2 pages), 30 sources, MLA, $ 118.95
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Abstract
The paper discusses how the many advances in data and text mining are already revolutionizing the librarian profession. The paper explores how the ability of data mining tools to extract, transfer and load (ETL) massive amounts of data at a single time, is changing how all tasks in an organization get completed.
Outline:
Executive Summary
Content Integration Is Key
Data Mining
i) Principles of Data Mining
ii) Data Mining Timeline
Data Mining Implications for Librarianship
Text Mining
i) Text Mining Timeline
ii) Data Mining versus Text Mining
iii) Mining Blogs: An Example of How Text Mining Works
Text Mining Implications for Librarianship
Conclusion
From the Paper
"At the intersection of text mining, linguistic analysis, statistical analysis, and latent semantic indexing techniques (Wikipedia Latent Semantic Indexing 2006). is the future of text mining that has the power to discover and report trending in highly unstructured content. At the center of text-mining's' rapid growth is the increasing sophistication of Natural Language Processing (CRM Buyer 2005). IBM and their significant research efforts in natural language processing are well documented on their website, as are the efforts and investments Microsoft is making."
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A Data Mining Review, 2006.
This paper discusses the increasing use of data mining in business today.
1,575 words (approx. 6.3 pages), 3 sources, $ 62.95
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Abstract
The paper explains that data mining is a process whereby enterprises or organizations in any industry approach their respective data and databases in a more constructive and targeted manner to produce actionable business strategies. As some researchers have observed, data mining and data warehousing are becoming more prevalent because of the large quantities of data stored in various systems and the number of business decisions made based on the data.
From the Paper
"Thus, data mining and data mining techniques have risen to prominence with the elevation in importance of databases and, more recently, the development of data warehouses that have changed the complexion of industry in all sectors. Data mining and data warehousing solutions have been especially important in customer relations management (CRM) and in the healthcare industries for example."
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Data Mining in Business Research, 2008.
A review on data mining's growth and a discussion on the different factors involved in text mining.
2,307 words (approx. 9.2 pages), 20 sources, MLA, $ 71.95
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Abstract
This paper relates that the use of data mining, its adjunct technologies for text mining and the ability to interpret, analyze and create linguistic models from unstructured content is revolutionizing the concept of data mining away from being purely used for structured content in data warehouses to now encompass unstructured content found throughout organizations globally.
The paper then provides insights into various areas of data mining, and the currently high levels of growth analytics use and applications software are experiencing as a result.
Outline:
Executive Summary
Using Data Mining in Business Research
Exploring the principles of Data Mining in Business Research
Predictive Methods in Data Mining
From the Paper
"A second predictive approach is called deviation detection. The purpose of this method is to discover the most significant changes in data from previously measured or median values. An example of the type of use for this predictive approach would be the development of strategies for selling tickets to frequent flyers who booked months in advance versus those that consistently book within a few weeks of their departure. A third approach to using data mining to predict future outcomes is using the classification approach, or technique. This predictive approach of classification uses a collection of records (training set) -- each record contains several attributes, one of them is the class (Ng & Han, 10). The task is to find a model for the class attribute as a function of other attributes, so, after that, previously unknown records can be assigned a very accurate class."
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Teleworkers and Data Security, 2008.
Analyzes research on telework in the federal government and data security and makes recommendations based on best practices to promote data security.
1,440 words (approx. 5.8 pages), 7 sources, APA, $ 47.95
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Abstract
This paper explains that the expansion of teleworking employment arrangements in the federal government has significant implications on organizations' data security and information technology operational strategies. The paper points out that telecommuting security concerns are an important area of study due to the sheer number of teleworkers, the rapidly changing information technology and the increase in remote access. The paper reveals several different solutions for the telework security problem; however, the most reasonable solution seems to be increased awareness and training regarding this problem. The paper also includes a section paraphrasing and summarizing source material and an extensive working annotated bibliography.
Outline:
Executive Summary
Literature Review
Recommended Solutions
Paraphrasing and Summarizing Source Material
Working Annotated Bibliography
From the Paper
"Of course, with every argument there is a counter-argument, and not all of the literature reviewed reports that teleworkers cause a greater threat to security. In fact there are some reports, such as one described by Sternstein (2007) that Federal teleworkers are actually less of a security threat than traditional office Federal workers. The report Sternstein is referring to comes from the Telework Exchange and explains that the reasons security threats are reduced via telework is that materials are not being physically transferred from place to place to place."
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How Data Is Managed In a Digital Computer, 2008.
This paper is an overview of computer data structure and the systems that enable the computer user to effectively manage the information within it.
1,755 words (approx. 7.0 pages), 1 source, MLA, $ 56.95
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Abstract
This paper describes that data structure is a way of storing data in a computer so that it can be used efficiently. The paper then goes on to describe how computers store the said data in terms of binary data presentations using Boolean logic. Furthermore, the paper describes data in the form of bits, along with converting binary data into decimals. Lastly, the paper talks about a computer's physical memory, which is based on one of two systems: (1) Random access memory (RAM), or (2) Read-only memory (ROM), and goes on to talk specifically about different coding systems.
From the Paper
"Data directly supported by CPU are called primary data type or machine data type computers. CPUs also process complex data type such as string, array, text files, databases, and image data such as MP3, jpeg, and mpeg. However, 64-bit and the 128-bit use different math functions in order to maintain portability. In each case, there is a signed and unsigned integer type associated with each. Excess notation is a format that is used to represent a signed integer and represents numbers in order and at the transition point; the high-order bit is set at zero. This represents the excess number. Positive numbers are above in order, negative below (Burd 78). Zero represents the excess identifier therefore; the excess 16 notation shows the value for zero is the bit pattern for 16 that is 10000."
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Data Mining, 2006.
Examines the benefits of data mining to an organization.
3,397 words (approx. 13.6 pages), 5 sources, MLA, $ 96.95
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Abstract
Data mining is the extraction of hidden predictive information from large databases. This paper examines the effect that data mining has on the current corporate climate. It defines data mining and examines the scope of its existence and effects on overall industry and the rest of the world. The paper also explains the basics of the technology behind data mining and how these tools will interact with localized software. Examples of how data mining technology can be profitably used, as well as how it will use the data warehouse architecture to evolve existing software to develop new ways to collect and interpret information, is also looked at.
From the Paper
"Model building itself is not a new technology; it is in fact something that has been around for a very long time. Since the beginning of computer technology, modeling has been a method to finding solutions. Computers work just as humans do by collecting information from a variety of differing situations and attempting to put it together in such a way that makes sense. With computers, there are more resources as well as faster integration of the information so the model building process is easy, fast and efficient. It also is much more complex than anything that a human can build which means the answer is in more depth and more accurate."
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Data Collection and Analysis Tools, 2005.
A look at the need for data collection and analysis tools, and the various relevant applications.
675 words (approx. 2.7 pages), 3 sources, $ 26.95
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Abstract
This paper discusses three articles on data collection and analysis tools and their applications. This includes data mining, data warehousing and software packages used in the collection. This paper also analyzes the needs of the business upon which the correct data collection and analysis tools are selected.
From the Paper
"Business today has more and more need for external consultants to use data collection and analysis tools in order to make assessment of business operations and processes. Many of the methods used today are computer-based, including software that does much of the job but still requires an able human operator to make decisions and input the correct information. Various analysts have made assessments of these methods to see how they are used and how effective they may be. Such tools are also used for analyzing performance in education, for assessing public programs, and for other tasks requiring a decision as to the value of a program or process. Bielski (2001) discusses the use of CRM, or Customer Resource Management system, which is used to track customer purchases while providing access to customer information using the computer. "
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Data Warehouse Management, 2002.
Researches and explains the importance of data warehouse management.
2,450 words (approx. 9.8 pages), 5 sources, APA, $ 74.95
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Abstract
Begins by defining data warehouse and describing the business uses for the technology. This is followed by a focus of data warehouse management. Three components of data warehouse management are examined. In addition, a discussion on the assurance of safety and privacy, which are needed to maintain the integrity of the data warehouse, is included. The discussion also focuses on the availability and reliability of the data warehouse. Finally the paper investigates different management tools that are used to maintain the data warehouse.
From the Paper
"Data warehouses are an indispensable part of any global organization. Data warehouses are used to keep track of sales, inventory, and customer spending patterns. (?Data Warehousing?) In fact, ?a data warehouse may contain very different things, ranging from the traditional financial, manufacturing, order and customer data, through document, legal and project data, on to the brave new world of market data, press, multi-media, and links to Internet and Intranet web sites.? (Barker 1998)"
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