Implementing A Data Warehouse
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Data Warehouse Systems
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Author : Alejandro Vaisman
language : en
Publisher: Springer
Release Date : 2014-09-10
Data Warehouse Systems written by Alejandro Vaisman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-10 with Computers categories.
With this textbook, Vaisman and Zimányi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes “Fundamental Concepts” including multi-dimensional models; conceptual and logical data warehouse design and MDX and SQL/OLAP. Subsequently, Part II details “Implementation and Deployment,” which includes physical data warehouse design; data extraction, transformation, and loading (ETL) and data analytics. Lastly, Part III covers “Advanced Topics” such as spatial data warehouses; trajectory data warehouses; semantic technologies in data warehouses and novel technologies like Map Reduce, column-store databases and in-memory databases. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Pentaho Business Analytics. All chapters are summarized using review questions and exercises to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available at http://cs.ulb.ac.be/DWSDIbook/, including electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style.
Data Warehousing
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Author : Mark Humphries
language : en
Publisher: Prentice Hall Professional
Release Date : 1999
Data Warehousing written by Mark Humphries and has been published by Prentice Hall Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
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Implementing A Data Warehouse
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Author : Bruce Russell Ullrey
language : en
Publisher: AuthorHouse
Release Date : 2007
Implementing A Data Warehouse written by Bruce Russell Ullrey and has been published by AuthorHouse this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
The purpose of this book is to document the methodology and chronology of work activity used by the author to successfully implement a Data Warehouse. Each of the eleven steps of the methodology is reviewed in the book, often using actual working documents as examples. The book contains lessons learned (both good and bad) as well as measures of success for each step. An essential aspect of DW project implementation (and other IT projects as well) is using established business practices to manage development and implementation. Discussion of use of these "due diligence" practices in Step 1 establishes the foundation for starting the DW project with the proper levels of management oversight. Step 2 presents examples of business models necessary for the DW developer to understand the needs of the business that the DW will serve. Other DW books describe the data modeling process but neglect to provide modeling instruction and actual examples to insure that the DW is properly aligned with business needs. An elegant data warehouse that doesn't meet the needs of the business is wasted effort. Step 3 documents and displays the level of detail needed to define CSF's (Critical Success Factors) and KPI's (Key Performance Indicators). If calculations for these important metrics are not defined in detail, and consensus to use them is not reached, then again, the most elegant data warehouse implementation is a wasted effort. In addition, developing and documenting functional requirements is essential in identifying legacy system reporting deficiencies. Step 4 describes how to access and display field level information on the iSeries platform. Actual shots of the resulting screens are shown. Step 5 presents the functional contents of an RFP for a Data Warehousing tool-set. Step 6 presents the progression of work required to build a data warehouse. Step 6 also: · Describes and displays a hybrid dimensional to flat file data model that may be, in reality, the best data organizational model for a typical data warehouse. Also, a table is included showing examples of data file field cryptic names and their corresponding metadata name. · &nb
Building A Data Warehouse
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Author : Vincent Rainardi
language : en
Publisher: Apress
Release Date : 2007-12-27
Building A Data Warehouse written by Vincent Rainardi and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-27 with Computers categories.
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.
Data Warehousing 101
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Author : Arshad Khan
language : en
Publisher: iUniverse
Release Date : 2003
Data Warehousing 101 written by Arshad Khan and has been published by iUniverse this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
Data Warehousing 101: Concepts and Implementation will appeal to those planning data warehouse projects, senior executives, project managers, and project implementation team members. It will also be useful to functional managers, business analysts, developers, power users, and end-users. Data Warehousing 101: Concepts and Implementation, which can be used as a textbook in an introductory data warehouse course, can also be used as a supplemental text in IT courses that cover the subject of data warehousing. Data Warehousing 101: Concepts and Implementation reviews the evolution of data warehousing and its growth drivers, process and architecture, data warehouse characteristics and design, data marts, multi-dimensionality, and OLAP. It also shows how to plan a data warehouse project as well as build and operate data warehouses. Data Warehousing 101: Concepts and Implementation also covers, in depth, common failure causes and mistakes and provides useful guidelines and tips for avoiding common mistakes.
Data Warehousing Fundamentals
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Author : Paulraj Ponniah
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-07
Data Warehousing Fundamentals written by Paulraj Ponniah and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-07 with Computers categories.
Geared to IT professionals eager to get into the all-importantfield of data warehousing, this book explores all topics needed bythose who design and implement data warehouses. Readers will learnabout planning requirements, architecture, infrastructure, datapreparation, information delivery, implementation, and maintenance.They'll also find a wealth of industry examples garnered from theauthor's 25 years of experience in designing and implementingdatabases and data warehouse applications for majorcorporations. Market: IT Professionals, Consultants.
Building A Scalable Data Warehouse With Data Vault 2 0
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Author : Daniel Linstedt
language : en
Publisher: Morgan Kaufmann
Release Date : 2015-09-15
Building A Scalable Data Warehouse With Data Vault 2 0 written by Daniel Linstedt and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Computers categories.
The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: - How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. - Important data warehouse technologies and practices. - Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. - Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast - Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse - Demystifies data vault modeling with beginning, intermediate, and advanced techniques - Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0
Data Warehousing In The Age Of Big Data
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Author : Krish Krishnan
language : en
Publisher: Newnes
Release Date : 2013-05-02
Data Warehousing In The Age Of Big Data written by Krish Krishnan and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-02 with Computers categories.
Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse. - Learn how to leverage Big Data by effectively integrating it into your data warehouse. - Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies - Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements
Fundamentals Of Data Warehouses
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Author : Matthias Jarke
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-11-26
Fundamentals Of Data Warehouses written by Matthias Jarke and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-11-26 with Computers categories.
This book presents the first comparative review of the state of the art and the best current practices of data warehouses. It covers source and data integration, multidimensional aggregation, query optimization, metadata management, quality assessment, and design optimization. A conceptual framework is presented by which the architecture and quality of a data warehouse can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modeling, and artificial intelligence.