Authored by Ralph Kimball and Margy Ross, known worldwide aseducators, consultants, and influential thought leaders in datawarehousing and business intelligence Begins with fundamental design recommendations and progressesthrough increasingly complex scenarios Presents unique modeling techniques for business applicationssuch as inventory management, procurement, invoicing, accounting,customer relationship management, big data analytics, and more Draws real-world case studies from a variety of industries,including retail sales, financial services, telecommunications,education, health care, insurance, e-commerce, and more Design dimensional databases that are easy to understand andprovide fast query response with The Data WarehouseToolkit: The Definitive Guide to Dimensional Modeling, 3rdEdition.
It shows how dimensional design fits in the overall lifecycle of planning, designing, developing, and deploying data marts and data warehouses. In other words, it covers ALL of the steps a developer needs to go through to guarantee a successful enterprise-wide data warehousing solution.
It also covers how to design data marts that are well integrated with the overall data warehouse architecture. Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram Just the FACTS studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram is Textbook Specific. Accompanys: This revised tutorial covers major lifecycle topics such as dimensional modeling, tech architecture, ETL, BI etc.
It is targeted at both novice and experienced data warehouse professionals. His first book, The Data Warehouse Toolkit, is the definitive guide to building a data warehouse. 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.
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. The book shows you all the practical details involved in planning, designing, developing, deploying, and growing data warehouses. The Data Webhouse Toolkit is a groundbreaking guide which introduces the Webhouse, a powerful new way of capturing valuable information flowing into a Web site and ordering it in ways that are useful to managers, strategic decision-makers, and customers.
Discussions of the most critical decision points for success at each phase of the data warehouse lifecycle help you understand ways in which both business and IT management can make decisions that best meet unified objectives. The world of data warehousing and business intelligence has changed remarkably since the first edition of The Data Warehouse Lifecycle Toolkit was published in Ralph Kimball and the Kimball Group refined the original set of lifecycle methods and techniques.
Project plan task list Download Chapter 3. Download Example pre-interview letter to brief interviewee. Download Example business user kickoff meeting agenda. Download Chapter 5. Download Sample product evaluation matrix. Download Metadata data model and create scripts. Download Chapter 7. Since then dimensional modelling has become the most widely accepted technique for data warehouse design. Since the first edition, Kimball has improved on his earlier techniques and created many new ones.
In this second edition, he provides a comprehensive collection of all of them, from basic to advanced, and strategies for optimising data warehouse design for common business applications.
He includes examples for retail sales, inventory management, procurement, orders and invoices, customer relationship management, accounting, financial services, telecommunication and utilities, health care, insurance and more. He also presents unique modelling techniques for e-commerce and shows strategies for optimising performance.
A companion Web site provides updates on dimensional modelling techniques, links to related sites and source code where appropriate. Score: 5. 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. This new third edition is a complete library of updateddimensional modeling techniques, the most comprehensive collectionever.
It covers new and enhanced star schema dimensional modelingpatterns, adds two new chapters on ETL techniques, includes new andexpanded business matrices for 12 case studies, and more. Authored by Ralph Kimball and Margy Ross, known worldwide aseducators, consultants, and influential thought leaders in datawarehousing and business intelligence Begins with fundamental design recommendations and progressesthrough increasingly complex scenarios Presents unique modeling techniques for business applicationssuch as inventory management, procurement, invoicing, accounting,customer relationship management, big data analytics, and more Draws real-world case studies from a variety of industries,including retail sales, financial services, telecommunications,education, health care, insurance, e-commerce, and more Design dimensional databases that are easy to understand andprovide fast query response with The Data WarehouseToolkit: The Definitive Guide to Dimensional Modeling, 3rdEdition.
The most authoritative guides from the inventor of the technique all for a value price. The Data Warehouse Toolkit, 3rd Edition Ralph Kimball invented a data warehousing technique called "dimensional modeling" and popularized it in his first Wiley book, The Data Warehouse Toolkit. Since this book was first published in , dimensional modeling has become the most widely accepted technique for data warehouse design.
Over the past 10 years, Kimball has improved on his earlier techniques and created many new ones. In this 3rd edition, he will provide a comprehensive collection of all of these techniques, from basic to advanced.
0コメント