Data Warehousing in the Real World
Data Warehousing in the Real World

Author: Sam Anahory

Publisher: Addison-Wesley Professional

Published: 1997

Total Pages: 0

ISBN-13: 9780201175196

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Data Warehouses are the primary means by which businesses can gain competitive advantage through analysing and using the information stored in their computerised systems. However, the Data Warehousing market is inundated with confusing, often contradictory, technical information from suppliers of hardware, databases and tools. Data Warehousing in the Real World provides comprehensive guidelines and techniques for the delivery of decision support solutions using open-systems Data Warehouses.Written by practitioners for practitioners Data Warehousing in the Real World describes each stage of the implementation process in detail: from project planning and requirements analysis, through architecture and design to administrative issues such as user access, security, back-up and recovery.Read this book to: - Learn the fundamentals of designing large-scale Data Warehouses using relational technology- Take advantage of product-independent comprehensive guidelines which cover all the issues you need to take into account when planning and building a Data Warehouse- Benefit from the authors' experience distilled into helpful hints and tips- Apply to your own situation with examples of real-life solutions taken from a variety of different business sectors- Make use of the templates for project-plans, system architectures and database designs provided in the appendixAbout the Authors: Sam Anahory is Director for Systems Integration at SHL Systemhouse (UK) where he runs their Data Warehousing practice, delivering Data Warehousing solutions to clients and managing the systems integration required. Prior to this, he built up and ran the Data Warehousing Practice for Oracle Corporation (UK).DennisMurray is a Principal consultant with Oracle Corporation (UK). While through being the Technical Architect for many Data Warehousing solutions, he has accumulated a vast amount of experience on a wide range of hardware platforms.Together they have collaborated on developing and giving training courses, workshops and presentations on the business and technical issues associated with delivering a Data Warehouse.

Data Warehousing in the Age of Big Data
Data Warehousing in the Age of Big Data

Author: Krish Krishnan

Publisher: Newnes

Published: 2013-05-02

Total Pages: 371

ISBN-13: 0124059201

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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

Modern Data Warehousing, Mining, and Visualization
Modern Data Warehousing, Mining, and Visualization

Author: George M. Marakas

Publisher:

Published: 2003

Total Pages: 300

ISBN-13:

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For undergraduate/graduate-level Data Mining or Data Warehousing courses in Information Systems or Operations Management Departments electives. Taking a multidisciplinary user/manager approach, this text looks at data warehousing technologies necessary to support the business processes of the twenty-first century. Using a balanced professional and conversational approach, it explores the basic concepts of data mining, warehousing, and visualization with an emphasis on both technical and managerial issues and the implication of these modern emerging technologies on those issues. Data mining and visualization exercises using an included fully-enabled, but time-limited version of Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software give students hands-on experience with real-world applications.

The Data Warehouse Toolkit
The Data Warehouse Toolkit

Author: Ralph Kimball

Publisher: John Wiley & Sons

Published: 2013-07-01

Total Pages: 608

ISBN-13: 1118732286

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Updated new edition of Ralph Kimball's groundbreaking book on dimensional modeling for data warehousing and business intelligence! The first edition of Ralph Kimball's The Data Warehouse Toolkit introduced the industry to dimensional modeling, and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds two new chapters on ETL techniques, includes new and expanded business matrices for 12 case studies, and more. Authored by Ralph Kimball and Margy Ross, known worldwide as educators, consultants, and influential thought leaders in data warehousing and business intelligence Begins with fundamental design recommendations and progresses through increasingly complex scenarios Presents unique modeling techniques for business applications such 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 and provide fast query response with The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition.

Data Mapping for Data Warehouse Design
Data Mapping for Data Warehouse Design

Author: Qamar Shahbaz

Publisher: Elsevier

Published: 2015-12-08

Total Pages: 181

ISBN-13: 0128053356

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Data mapping in a data warehouse is the process of creating a link between two distinct data models' (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle. - Covers all stages of data warehousing and the role of data mapping in each - Includes a data mapping strategy and techniques that can be applied to many situations - Based on the author's years of real-world experience designing solutions

Data Warehousing
Data Warehousing

Author: Mark Humphries

Publisher: Prentice Hall Professional

Published: 1999

Total Pages: 384

ISBN-13: 9780130809025

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Emerging Perspectives in Big Data Warehousing
Emerging Perspectives in Big Data Warehousing

Author: Taniar, David

Publisher: IGI Global

Published: 2019-06-28

Total Pages: 366

ISBN-13: 152255517X

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The concept of a big data warehouse appeared in order to store moving data objects and temporal data information. Moving objects are geometries that change their position and shape continuously over time. In order to support spatio-temporal data, a data model and associated query language is needed for supporting moving objects. Emerging Perspectives in Big Data Warehousing is an essential research publication that explores current innovative activities focusing on the integration between data warehousing and data mining with an emphasis on the applicability to real-world problems. Featuring a wide range of topics such as index structures, ontology, and user behavior, this book is ideally designed for IT consultants, researchers, professionals, computer scientists, academicians, and managers.

E-Data
E-Data

Author: Jill Dyché

Publisher: Addison-Wesley Professional

Published: 2000

Total Pages: 374

ISBN-13: 9780201657807

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Dyche presents the complete manager's briefing on what data warehousing technology can do today and how to achieve optimal results. Using real-world case studies from Charles Schwab, Bank of America, Qantas, 20th Century Fox, and others, she covers decision support, database marketing, and many industry-specific data warehouse applications.

The Data Warehouse Toolkit
The Data Warehouse Toolkit

Author: Ralph Kimball

Publisher: John Wiley & Sons

Published: 2011-08-08

Total Pages: 464

ISBN-13: 1118082141

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This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.