Mastering Data Warehouse Aggregates: Solutions for Star Schema Performance

Definition

• The selection and design, the load from a star schema aggregates used in dimensional modeling of the first book to provide in-depth coverage and use for specific tasks and the results of demonstration projects
• Global navigation and basic design principles of a global and covers the advantages and disadvantages of different types of business solutions
• This development projects data storage throughout, including the growing importance of explaining development, first creates and loads the data from the iterative

Back cover

The first book that offers in-depth coverage of the star maps overview

As the most effective method for maximizing star schema performance Dubbed by Ralph Kimball aggregates of dimensions more spectacular than any other technology is a powerful and effective tool to accelerate data warehouse queries. Well structured and implemented a database after verifying that it was built, the overall performance of data storage must begin with the measures taken.

However, many companies solve performance problems, rather than turn to aggregate custom hardware and proprietary software products to ignore. This book fills a gap in knowledge has led companies to costly and risky.

A series of well-planned data warehouse expert Chris Adamson overall have a significant effect on overall performance indicates that the data store. A role in avoiding common pitfalls, or whatever the current level of star schema information, best practices in this book, we will help you get an incredible performance increase.

Collection techniques have progressed from the database schema stars, tables, and the impact of the life cycle of this book covers the entire data storage. The approach of design data, including the warehouse star schema, after establishing some key areas, the articles on shelf-life data of the main phases. Topics are:

• The basic design principles of the global schema
• With or without the addition of a browser, how aggregate is used in a production environment
• Integration with ETL processing a total
• The standard tasks of development projects and data storage products that contain additives
• How overall existing star schema adds the ability to organize and execute a project
• The aggregation of bridge tables, stars such heterogeneous models or the instantaneous impact and plans advanced design
• Incorporate three-dimensional aggregates with life the views or IBM Oracle Implementation of special considerations query the tables
• How comprehensive, including security database and archiving strategy can add value in other areas

Wiley Publishing Technology timely. Practice. Reliable.

Www.wiley.com / compbooks / visit our website at

About the Author

Christopher Adamson, data storage consultant and founder of Oakton Software LLC. Directed and implemented a variety of industries, applications star schema data warehouse, an expert in the design. Its clients Fortune 500 companies, small and large businesses, government agencies and providers of data storage devices, we have included. Dimensional Modeling and Data Warehouse Design Solutions Adamson also (also from Wiley) teaches author. O, on its website, can be reached through www.ChrisAdamson.net.

DW 2.0: The Architecture for the Next Generation of Data Warehousing (Morgan Kaufman Series in Data Management Systems)

Data warehousing has been around for 20 years and became part of the IT infrastructure. Non-data - data storage for the original information was developed in response to business needs and integrated data, provides granular institutions, and history.

Development paths and stores data in large part to different types of providers of software and hardware, there are many types. But in numerous speeches, articles, and reached its 65,000 professional b-eye Network-months notice, as defined by the author DW 2.0, well identified and defined next generation data storage.

The book takes this theme and the future of data storage and the level of the architecture and the level of technology, says it is now technologically possible. The book was a top-down perspective: looking at the overall architecture and then dive into the issues underlying the components. Building a data warehouse for people who use or see this advantage and can determine what the future: what to buy the new technology, data warehouse, how to plan extensions to warrant expenditure and how you can save the current system - in practice.

This data warehouse professional everything and gives full experience of what it takes to implement a new generation DW 2.0.

• The first book is a new generation of data warehouse architecture, DW 2.0.
• "Father of the data warehouse", Bill INMO, a newspaper columnist and editor of Channel INMO the bill written by the Business Intelligence Network.
• A technology that provides the next generation of vehicles and the overall implementation long delay coverage DW: metadata, temporal data, unstructured data ETL, quality control data.

The Data Warehouse Lifecycle Toolkit

Design, development and implementation of data warehouse and business intelligence systems, the industry standard for a full update

Data Warehouse Lifecycle Toolkit, since the first edition published in 1998, significantly changed the world of data storage. At that time, the data storage industry has come of age and advances of acceptance, the hardware and software have been incredible, and the first edition of this book promotion techniques have been adopted by almost all storage vendors and professionals in the data. Discuss the data source systems, cleaning, and add value to the delivery business: In addition, the "business intelligence" turned out to reflect long-term mission of the data warehouse.

Ralph Kimball and his colleagues, the methods of consultation and training based on their experience and their life cycle techniques have refined the original series. The authors first-hand data warehouse / business intelligence to understand the (DW / BI) will turn around faster than the organization needs to change. To this end, a system design DW / BI, develop, and is guided by the detailed steps to implement. They make better business decisions and the adaptive system that allows business users to learn how to create and analyze data.

Important new content and updates, this second edition of Data Warehouse Lifecycle Toolkit again sets the standard data storage for the next ten years. Shows you how to:

• The data warehouse to identify and prioritize opportunities
• Create an architectural plan, select and products
• Model Flexible strong design size
• Create robust ETL
• Develop BI applications to provide data for professional users
• Good DW / BI environment, implement, and maintain

Kimball, a member of the writers. Each of the data warehouse and business intelligence consulting and training for over 15 years focused on the tools I've written other books in the series. Kimball Group and Kimball University learn more about www.kimballgroup.com.

With the three following books: The book also Kimball Warehouse Toolkit Classics Box Set (9780470479575 ISBN) can be used as part of the data obtained from:

• Data Warehouse Toolkit, 2nd Edition (9780471200246)
• Data Warehouse Lifecycle Toolkit, 2nd Edition (9780470149775) 
• Data Warehouse ETL Toolkit (9780764567575)

The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning

Books with previous sold over 150,000 copies by Ralph Kimball, the world authority on data storage by the co-writer

• The storage time and labor data offers concrete solutions for the most part of the test data, or load, process, retrieve data (ETL) 
• Extracting data from scattered sources, removing redundant and inaccurate data, the remaining data in the data structures correctly and then load the final product in the store is based on best practices for data 
• Proven and time-saving ETL techniques, the overall direction of building dimensional structures and guidance essential to the quality of data offers

About the Author

Ralph Kimball, Ph.D., founder of the Kimball Group, is a visionary industry leader in data storage since 1982 and is now one of the best known speakers and educators. She Data Warehouse Toolkit (Wiley), including the bestselling titles published in multiple data stores, the author.

Joe Caserta Concepts, LLC, for data storage is the founder of a consulting firm. He writes often for print and online magazines, and more for data storage professionals actively contribute DWList, online community.

The Kimball Group Reader: Relentlessly Practical Tools for Data Warehousing and Business Intelligence

The proposed rules for the data warehouse and business intelligence, and a unique collection of Ralph Kimball Group colleagues developed by the team.

The leaders of industry data storage, known as the most effective and respected throughout the world, Ralph Kimball and Kimball Group to define the area of ? Data storage 250 that contains the articles written on the subject. For the first time, the board Kimball Group's unique design tips and best practices, covering a decade of innovation in data storage, articles collected in this extraordinary collection.

Kimball is a global life-cycle methodology developed by the original with comments explaining the roles of each group of items offered. This practical, hands-product fully reflects current practices and terminology planning and project requirements gathering, dimensional modeling, ETL and business intelligence and analysis, including updates for cover the entire life cycle.

In any capacity, whether or not related to data storage and business intelligence is nothing more important for the easy reference of this collection.

Detailed data and storage practices and business intelligence, most authoritative guides to the collection

Over the past 15 years, Ralph Kimball and his team, his friends a unique data warehouse (DW) in the field have come to define the topic with more than 250 articles I wrote. Kimball, group thinking and practices to reflect the reader, most of these articles have completely updated. Project planning, requirements gathering, dimensional modeling, ETL and Business Intelligence (BI) and analysis, including full life cycle, the lining, the authors go beyond Toolkit extends the detailed requirements and provide technical advice to new ideas and best practices.

Ideas drive data storage and the principles established by a group of articles begin. The following content is available for your own projects, with a deep and practical guide gives detailed information on each stage of the life cycle of data storage. After the project, including needs and business planning, the authors, while taking a bath in three dimensions. Articles in over 100 one-dimensional modeling. These items are fully revised and updated as necessary to reflect best practices established by the Kimball Group, has been extended.

Design, implementation, and the reader is Kimball Group DW / BI, recommended to protect the critical success with unique items

• Dos and don'ts for collecting requirements
• Kimball, enterprise data storage and matrix architecture
• Duties and Responsibilities dimensional modeling
• In fact, the basic concepts of the table and dimension table
• Sizes of data management are not appropriate
• Granularity, and indeed the three basic types of table
• Snowflakes and stabilizers
• Value and characteristics of multiple hierarchies of unequal size, data transfer and bridges
• Customer size and scope Shadow of internationalization
• Slow development and size of the hybrids
• Subsystems (ETL), Extract Transform and Load
• Advantages and disadvantages of using a commercial ETL tool
• Focused analytics server architecture, data management, and packaged
• Forequarter BI applications and data mining
• Techniques mature DW / BW environment, evaluation, and return to the road

About the Author

Ralph Kimball, Ph.D., founder of Kimball and a visionary leader in data storage industry.

Kimball, Margy Ross, group president since 1982 and only the solutions DW / BI focused on.