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Author: Julio Bolton
Publisher: Larsen and Keller Education
ISBN: 9781641720731
Category :
Languages : en
Pages : 189
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Book Description
A data warehouse (DW) is a system used in computing for data analysis and reporting. It is a core component of business intelligence. It stores integrated historical and current data from one or more sources. Data can be characterized according to data integration, time-variance, subject orientation, volatility, granularity, etc. It is then arranged into groups, facts and aggregate facts. The sources of data are cleansed, catalogued, transformed and used for data mining, market research, decision support and online analytical processing. The ways to analyze or retrieve the data, transform, load and extract data and manage the data dictionary are essential components of a data warehousing system. Data warehouses can be designed using the bottom-up, top-down or hybrid design models. This book aims to shed light on some of the unexplored aspects of data warehousing. Most of the topics introduced herein cover new techniques and applications of this field. Those in search of information to further their knowledge will be greatly assisted by this textbook.
Author: Julio Bolton
Publisher: Larsen and Keller Education
ISBN: 9781641720731
Category :
Languages : en
Pages : 189
Get Book Here
Book Description
A data warehouse (DW) is a system used in computing for data analysis and reporting. It is a core component of business intelligence. It stores integrated historical and current data from one or more sources. Data can be characterized according to data integration, time-variance, subject orientation, volatility, granularity, etc. It is then arranged into groups, facts and aggregate facts. The sources of data are cleansed, catalogued, transformed and used for data mining, market research, decision support and online analytical processing. The ways to analyze or retrieve the data, transform, load and extract data and manage the data dictionary are essential components of a data warehousing system. Data warehouses can be designed using the bottom-up, top-down or hybrid design models. This book aims to shed light on some of the unexplored aspects of data warehousing. Most of the topics introduced herein cover new techniques and applications of this field. Those in search of information to further their knowledge will be greatly assisted by this textbook.
Author: Paulraj Ponniah
Publisher: John Wiley & Sons
ISBN: 0471463892
Category : Computers
Languages : en
Pages : 544
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Book Description
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.
Author: Matthias Jarke
Publisher: Springer Science & Business Media
ISBN: 9783540420897
Category : Computers
Languages : en
Pages : 328
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Book Description
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.
Author: Robert Stackowiak
Publisher: John Wiley & Sons
ISBN: 047012718X
Category : Computers
Languages : en
Pages : 410
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Book Description
Up-to-date, comprehensive coverage of the Oracle database and business intelligence tools Written by a team of Oracle insiders, this authoritative book provides you with the most current coverage of the Oracle data warehousing platform as well as the full suite of business intelligence tools. You'll learn how to leverage Oracle features and how those features can be used to provide solutions to a variety of needs and demands. Plus, you'll get valuable tips and insight based on the authors' real-world experiences and their own implementations. Avoid many common pitfalls while learning best practices for: Leveraging Oracle technologies to design, build, and manage data warehouses Integrating specific database and business intelligence solutions from other vendors Using the new suite of Oracle business intelligence tools to analyze data for marketing, sales, and more Handling typical data warehouse performance challenges Uncovering initiatives by your business community, security business sponsorship, project staffing, and managing risk
Author: W. H. Inmon
Publisher: John Wiley & Sons
ISBN: 0471270482
Category : Computers
Languages : en
Pages : 434
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Book Description
The data warehousing bible updated for the new millennium Updated and expanded to reflect the many technological advances occurring since the previous edition, this latest edition of the data warehousing "bible" provides a comprehensive introduction to building data marts, operational data stores, the Corporate Information Factory, exploration warehouses, and Web-enabled warehouses. Written by the father of the data warehouse concept, the book also reviews the unique requirements for supporting e-business and explores various ways in which the traditional data warehouse can be integrated with new technologies to provide enhanced customer service, sales, and support-both online and offline-including near-line data storage techniques.
Author: Krish Krishnan
Publisher: Newnes
ISBN: 0124059201
Category : Computers
Languages : en
Pages : 371
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Book Description
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
Author: Ralph Kimball
Publisher: John Wiley & Sons
ISBN: 1118732286
Category : Computers
Languages : en
Pages : 608
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Book Description
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.
Author: Jill Dyché
Publisher: Addison-Wesley Professional
ISBN: 9780201657807
Category : Business & Economics
Languages : en
Pages : 374
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Book Description
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.
Author: Parteek Bhatia
Publisher: Cambridge University Press
ISBN: 110858585X
Category : Computers
Languages : en
Pages : 514
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Book Description
Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.
Author: Ralph Hughes
Publisher: Newnes
ISBN: 0123965187
Category : Computers
Languages : en
Pages : 563
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Book Description
Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: - Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked. - Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs. - Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines. Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way. - Learn how to quickly define scope and architecture before programming starts - Includes techniques of process and data engineering that enable iterative and incremental delivery - Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing - Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges - Use the provided 120-day road map to establish a robust, agile data warehousing program
