Building a Data Warehouse: With Examples in SQL Server (Expert's Voice) eBook: Vincent Rainardi: Amazon.it: Kindle Store

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Descrizione prodotto

Sinossi

Building a Data Warehouse: With Examples in SQL Server describes how to build a data warehouse completely from scratch and shows practical examples on how to do it. 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. The relational database management system (RDBMS) used in the examples is SQL Server; the version will not be an issue as long as the user has SQL Server 2005 or later.

The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. 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. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation.

What you’ll learn

A detailed understanding of what it takes to build a data warehouse
The implementation code in SQL Server to build the data warehouse
Dimensional modeling, data extraction methods, data warehouse loading, populating dimension and fact tables, data quality, data warehouse architecture, and database design
Practical data warehousing applications such as business intelligence reports, analytics applications, and customer relationship management

Who this book is for

There are three audiences for the book. The first are the people who implement the data warehouse. This could be considered a field guide for them. The second is database users/admins who want to get a good understanding of what it would take to build a data warehouse. 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.

L'autore

A bio is not available for this author.

Dettagli prodotto

Formato: Formato Kindle
Dimensioni file: 9054 KB
Lunghezza stampa: 526
Numeri di pagina fonte ISBN: 1590599314
Editore: Apress; 1 edizione (21 dicembre 2007)
Venduto da: Amazon Media EU S.� r.l.
Lingua: Inglese
ASIN: B001AUPQ8A
Da testo a voce: Abilitato

X-Ray: Non abilitato

Posizione nella classifica Bestseller di Amazon: #114.397 a pagamento nel Kindle Store (Visualizza i Top 100 a pagamento nella categoria Kindle Store)

Recensioni clienti

Le recensioni clienti pi� utili su Amazon.com ^(beta)

Amazon.com: 4.8 su 5 stelle 9 recensioni

14 di 14 persone hanno trovato utile la seguente recensione

3.0 su 5 stelle Heavy on practical tips, light on general principles 7 ottobre 2008

Di Christoffer Swanstrom - Pubblicato su Amazon.com

Formato:Rilegato|Acquisto verificato Amazon

A very hands-on book about implementing a Data Warehouse using Microsoft SQL Serveer 2005. In fact, it is a bit too hands-on in the sense that it guides you through all clicks and keystrokes but is rather thin and vague on general design principles.

The author has set out to write "a book containing all the essential subjects of building a data warehouse" (quote from the introduction). However, given the breadth of the material the author tries to cover (and given the sometimes annoyingly plentiful screenshots and SQL code) there is not enough room to give the necessary background and generalize the examples enough to be more useful than just that, examples.

For a much better attempt to cover both principles and a specific platform, a much better choice is The Microsoft Data Warehouse Toolkit (by Joy Mundy and Warren Thornthwaite), also covering SQL Server 2005.

For someone looking for just the practical part on how to use the Microsoft tools (SQL Server, SSIS, SSAS) to implement a Data Warehouse and already knows the general principles of data warehousing is probably better off buying a book or several books that cover just those specific tools.

8 di 8 persone hanno trovato utile la seguente recensione

5.0 su 5 stelle Definitely a book for the doers, excellent ETL part 23 giugno 2008

Di Jiang Tang - Pubblicato su Amazon.com

Formato:Rilegato

I have read all the major DW books for sql server. All of them fall short in practicality. This book is deceivingly thin (500 some pages), but it covers all the practical side of building a data warehouse using SQL server 2005. The author's experience shows through his handling of many of the practical issues encountered in implementing data warehouse. This book has excellent coverage on ETL process, oftentimes list several alternatives that suited people from different background.

7 di 8 persone hanno trovato utile la seguente recensione

5.0 su 5 stelle An essential read. Practical & easy to understand. 7 marzo 2008

Di SQL DBA/Developer - Pubblicato su Amazon.com

Formato:Rilegato

This book is a must read for anyone embarking on a Data Warehouse project or who wants to learn more about a particular aspect of Data Warehousing. The book guides the reader through the principles underpinning Data Warehousing, with easy to understand definitions. It gives detailed insight into the design, build & testing phases essential to any successful Data Warehousing project. It even covers reporting; including using the Data Warehouse for Business Intelligence and Customer Relationship Management. Throughout the book the author describes potential problems and gives techniques on how to overcome them.
There are tons of practical examples from an author who has a wealth of technical experience in this field.

This book is highly recommended.

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I pi� evidenziati

storing the history of the master data is one of the key features. This is known as a slowly changing dimension (SCD). A slowly changing dimension is a technique used in dimensional modeling for preserving historical information about dimensional data. &quote;

Evidenziato da 5 utenti Kindle

A dimensional data store is a better format to store data in the warehouse for the purpose of querying and analyzing data than a normalized data store. &quote;

Evidenziato da 5 utenti Kindle

A data warehouse system has two main architectures: the data flow architecture and the system architecture. The data flow architecture is about how the data stores are arranged within a data warehouse and how the data flows from the source systems to the users through these data stores. The system architecture is about the physical configuration of the servers, network, software, storage, and clients. &quote;

Evidenziato da 5 utenti Kindle

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