First independent book on data virtualization that explains in a product-independent way how data virtualization technology works. Illustrates concepts using examples developed with commercially available products. Oracle Essentials provides the conceptual background you need to understand how Oracle truly works. I recommend reading this Data Warehouse Lifecycle Toolkit 2nd Edition Pdf Kindle because this book contains many positive messages for us. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. Are you looking for Data Warehouse Lifecycle Toolkit 2nd Edition Pdf ePub eBook to Download or read.
In order to facilitate the needed steps when handling a dataanalysis or data mining project, a step-by-step approach aidsprofessionals in carefully analyzing data and implementing results,leading to the development of smarter business decisions. Kimball uses actual case studies of existing data warehouses developed for specific types of business applications such as retail, manufacturing, banking, insurance, subcriptions and airline reservations. Each chapter describes one of sixteen development steps and the major activities, deliverables, roles, and responsibilities. In this 3rd edition, he will provide a comprehensive collection of all of these techniques, from basic to advanced. It also covers how to design data marts that are well integrated with the overall data warehouse architecture. Complete with illustrations and helpful hints, this fifth edition provides a valuable one-stop overview of Oracle Database 12c, including an introduction to Oracle and cloud computing.
Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume. It also cover more advanced techniques for specific industries, such as financial services, telecommunications and utilities, health care, insurance and more. Understand the big picture of data virtualization and its relationship with data governance and information management. Bottom line, this book provides the insight to help companies combine Internet-based business intelligence with the bounty of customer data generated from the internet. It is targeted at both novice and experienced data warehouse professionals. This new third edition is a complete library of updateddimensional modeling techniques, the most comprehensive collectionever.
The Data Warehouse Lifecycle Toolkit, 2nd Edition 9780470149775 Complete coverage of best practices from data warehouse project inception through on-going program management. You'll learn to create adaptable systems that deliver data and analyses to business users so they can make better business decisions. The book is organized as follows. His first book, The Data Warehouse Toolkit, is the definitive guide to building a data warehouse. The book offers a principled overview of key implementation techniques that are particularly important to multidimensional databases, including materialized views, bitmap indices, join indices, and star join processing. The authors conclude by crystallizing their many years of experience in a list of dos, don'ts, tips, and rules of thumb.
This coverage includes advanced dimension-related concepts such as slowly changing dimensions, degenerate and junk dimensions, outriggers, parent-child hierarchies, and unbalanced, non-covering, and non-strict hierarchies. It shows you how to use data to help make decisions about strategies to improve student achievement. The first edition of Ralph Kimball's The Data WarehouseToolkit introduced the industry to dimensional modeling,and now his books are considered the most authoritative guides inthis space. All technical material is clearly expressed in tables, graphs, and diagrams. Star Schema: The Complete Reference offers in-depth coverage of design principles and their underlying rationales. Kimball explains the key elements of the Webhouse and provides detailed guidelines for designing, building, and managing the Webhouse. Now, he carries these techniques to the larger issues of delivering complete data marts and data warehouses.
Companies can use this information to determine buying habits, provide customers with recommendations on new products, and much more. Author Vincent Rainardi also describes some practical issues he has experienced that developers are likely to encounter in their first data warehousing project, along with solutions and advice. Management tools, such as graphs illustrating the timing and coordination of activities, are included throughout the book. . If designed and deployed correctly, the Webhouse can become the linchpin of the modern, customer-focused company, providing competitive information essential to managers and strategic decision makers. Publishers About Privacy Terms Help.
Apply data virtualization right away with three chapters full of practical implementation guidance. The Second Edition isalso an ideal textbook for undergraduate and graduate-level coursesin data analysis and data mining and is appropriate forcross-disciplinary courses found within computer science andengineering departments. About 30 to 40% of the content in the book is updated and new. In this groundbreaking guide, data warehousing's bestselling author, Ralph Kimball, introduces readers to the Data Webhouse--the marriage of the data warehouse and the Web. All books are in clear copy here, and all files are secure so don't worry about it. This could be considered a field guide for them.
The first are the people who implement the data warehouse. Over the past 10 years, Kimball has improved on his earlier techniques and created many new ones. Finally, the third audience is managers who must make decisions about aspects of the data warehousing task before them and use the book to learn about these issues. Using the techniques learned in Kimball's first book, The Data Warehouse Lifecycle Toolkit carries them to the larger issues of delivering complete data marts and data warehouses. This all-inclusive volume begins with dimensional design fundamentals and shows how they fit into diverse data warehouse architectures, including those of W. Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization.
Visit Kindle Store for the book blurb, ratings and customer reviews. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data. It shows how dimensional design fits in the overall lifecycle of planning, designing, developing, and deploying data marts and data warehouses. The authors walk readers through every step of the process--from strategic planning to the selection of new technologies and the evaluation of application releases. The authors show developers the best methods for extracting data from scattered sources throughout the enterprise, removing obsolete, redundant, and innaccurate data, transforming the remaining data into correctly formatted data structures, and then physically loading them into the data warehouse. After your application is in production, you need to understand how to administer data warehouse operation. Unfortunately, many companies fail to take full advantage of this deluge of information because they lack the necessary resources to effectively analyze it.