DATA WAREHOUSING. FUNDAMENTALS. A Comprehensive Guide for. IT Professionals. PAULRAJ PONNIAH. A Wiley-Interscience. Library of Congress Cataloging-in-Publication Data: Ponniah, Paulraj. Data warehousing fundamentals for IT professionals / Paulraj Ponniah. Data Warehousing Fundamentals for it Professionals, Second Edition. Author(s). Paulraj Ponniah. First published May Print ISBN
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Repo for Data Warehouse Concepts, Design, and Data Integration by University of Colorado System (coursera)(Notes,Assignments, quiz and research papers). DOWNLOAD PDF The Compelling Need for Data Warehousing Chapter Objectives 1 Escalating Need for Strategic Information 2 .. professionals about my faculty colleague Paulraj Ponniah's textbook Data Warehousing Fundamentals. Library of Congress Cataloging-in-Publication Data: Ponniah, Paulraj. Data warehousing fundamentals for IT professionals / Paulraj Ponniah.—2nd ed. p. cm .
This is the one definitive book on data warehousing clearly intended for IT professionals. The organization and presentation of the book are specially tuned for IT professionals.
This book does not presume to target anyone and everyone remotely interested in the subject for some reason or another, but is written to address the specific needs of IT professionals like you. It does not tend to emphasize certain aspects and neglect other critical ones.
The book takes you over the entire landscape of data warehousing. How can this book be exactly suitable for IT professionals? As a veteran IT professional with wide and intensive industry experience, as a successful database and data warehousing consultant for many years, and as one who teaches data warehousing fundamentals in the college classroom and in public seminars, I have come to appreciate the precise needs of IT professionals, and in every chapter I have incorporated these requirements of the IT community.
Why is there a tremendous surge in interest? Data warehousing is no longer a purely novel idea just for research and experimentation. It has become a mainstream phenomenon. More than half of all U. In every industry across the board, from retail chain stores to financial institutions, from manufacturing enterprises to government departments, and from airline companies to utility businesses, data warehousing is revolutionizing the way people perform business analysis and make strategic decisions.
Every company that has a data warehouse is realizing the enormous benefits translated into positive results at the bottom line. These companies, now incorporating Web-based technologies, are enhancing the potential for greater and easier delivery of vital information. Over the past five years, hundreds of vendors have flooded the market with numerous data warehousing products.
Vendor solutions and products run the gamut of data warehousing—data modeling, data acquisition, data quality, data analysis, metadata, and so on.
The market is already large and continues to grow. IT is no longer required to create every report and present every screen for providing information to the end-users.
IT is now charged with the building of information delivery systems and letting the end-users themselves retrieve information in innovative ways for analysis and decision making.
Data warehousing is proving to be just that type of successful information delivery system. IT professionals responsible for building data warehouses need to revise their mindsets about building applications.
They have to understand that a data warehouse is not a onesize-fits-all proposition; they must get a clear understanding of the extraction of data from source systems, data transformations, data staging, data warehouse architecture, infrastructure, and the various methods of information delivery. In short, IT professionals, like you, must get a strong grip on the fundamentals of data warehousing.
You will be able to study every significant topic in planning, requirements, architecture, infrastructure, design, data preparation, information delivery, deployment, and maintenance. It is specially designed for IT professionals; you will be able to follow the presentation easily because it is built upon the foundation of your background as an IT professional, your knowledge, and the technical terminology familiar to you.
It is organized logically, beginning with an overview of concepts, moving on to planning and requirements, then to architecture and infrastructure, on to data design, then to information delivery, and concluding with deployment and maintenance. The book provides an interactive learning experience. It is not a one-way lecture. You participate through the review questions and exercises at the end of each chapter.
For each chapter, the objectives set the theme and the summary provides a list of the topics covered. You can relate each concept and technique to the data warehousing industry and marketplace.
You will notice a substantial number of industry examples. Although intended as a first course on fundamentals, this book provides sufficient coverage of each topic so that you can comfortably proceed to the next step of specialization for specific roles in a data warehouse project.
Featuring all the significant topics in appropriate measure, this book is eminently suitable as a textbook for serious self-study, a college course, or a seminar on the essentials. It provides an opportunity for you to become a data warehouse expert. I acknowledge my indebtedness to the authors listed in the reference section at the end of the book.
Their insights and observations have helped me cover adequately the topics. I must also express my appreciation to my students and professional colleagues.
Our interactions have enabled me to shape this textbook according to the needs of IT professionals. You have been involved in the design, implementation, and maintenance of systems that support day-to-day business operations. Depending on the industries you have worked in, you must have been involved in applications such as order processing, general ledger, inventory, in-patient billing, checking accounts, insurance claims, and so on.
These applications are important systems that run businesses. They process orders, maintain inventory, keep the accounting books, service the clients, receive payments, and process claims. Without these computer systems, no modern business can survive. Companies started building and using these systems in the s and have become completely dependent on them. As an enterprise grows larger, hundreds of computer applications are needed to support the various business processes.
These applications are effective in what they are designed to do. They gather, store, and process all the data needed to successfully perform the daily operations. They provide online information and produce a variety of reports to monitor and run the business.
In the s, as businesses grew more complex, corporations spread globally, and competition became fiercer, business executives became desperate for information to stay competitive and improve the bottom line. This institution has since emerged as the leading voice in the data warehousing and business intelligence arena providing education, research, and support.
Expansion of globalization opened the arena for competitors, more in number and greater in power. New privacy regulations created the need to revise methods of collection and use of information.
Improper architecture of some initial data warehousing systems produced fragmented views of corporate data and tended to produce disparate information silos. Query, reporting, and analysis tools provided to the users in the early data warehousing environments for self-service proved to be too complex and overwhelming for use by the users themselves. Companies began to perceive that the goal of decision-support systems is twofold: transformation of data to information; derivation of knowledge from information.
Each of these two aspects needs to be emphasized and strengthened appropriately to provide the necessary results. Business intelligence for an organization requires two environments, one to concentrate on transformation of data into information and the other to deal with transformation of information into knowledge.
Business intelligence BI , therefore, is a broad group of applications and technologies. First, the term refers to the systems and technologies for gathering, cleansing, consolidating, and storing corporate data.
Next, business intelligence relates to the tools, techniques, and applications for analyzing the stored data.
The Gartner Group popularized BI as an umbrella term to include concepts and methods to improve business decision making by fact-based support systems. In this environment data from multiple operational systems are extracted, integrated, cleansed, transformed and stored as information in specially designed repositories. Information to Knowledge. In this environment analytical tools are made available to users to access and analyze the information content in the specially designed repositories and turn information into knowledge.
Again, using this information with sophisticated tools for proper decision making is equally challenging. Therefore, the trend is to consider these as two distinct environments for corporate BI.
Vendors also tend to specialize in tools appropriate for these two distinct environments. However, the two environments are complementary and need to work together. Figure shows the two complementary environments, the data warehousing environment, which transforms data into information, and the analytical environment, which produces knowledge from information. As we proceed from chapter to chapter, we will keep expanding and intensifying our discussion of these two environments.
In spite of tons of data accumulated by enterprises over the past decades, every enterprise is caught in the middle of an information crisis. Information needed for strategic decision making is not readily available.
All the past attempts by IT to provide strategic information have been failures. This was mainly because IT has been trying to provide strategic information from operational systems. Informational systems are different from the traditional operational systems. Operational systems are not designed for strategic information. We need a new type of computing environment to provide strategic information.
The data warehouse promises to be this new computing environment. Data warehousing is the viable solution. I hope all links work properly because,these links are not operated by us. All links are found by web search over the different sites. It is very comprehensive and interesting subject also easy to score marks. Life cycle of data,What is Data Mining? So,you can read it and practice more to get good score on this particular subject.
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