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Dw 2 0 The Architecture For The Next Generation Of Data Warehousing

Author: W.H. Inmon
Publisher: Elsevier
ISBN: 9780080558332
Size: 38.62 MB
Format: PDF, Docs
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DW 2.0: The Architecture for the Next Generation of Data Warehousing is the first book on the new generation of data warehouse architecture, DW 2.0, by the father of the data warehouse. The book describes the future of data warehousing that is technologically possible today, at both an architectural level and technology level. The perspective of the book is from the top down: looking at the overall architecture and then delving into the issues underlying the components. This allows people who are building or using a data warehouse to see what lies ahead and determine what new technology to buy, how to plan extensions to the data warehouse, what can be salvaged from the current system, and how to justify the expense at the most practical level. This book gives experienced data warehouse professionals everything they need in order to implement the new generation DW 2.0. It is designed for professionals in the IT organization, including data architects, DBAs, systems design and development professionals, as well as data warehouse and knowledge management professionals. * First book on the new generation of data warehouse architecture, DW 2.0. * Written by the "father of the data warehouse", Bill Inmon, a columnist and newsletter editor of The Bill Inmon Channel on the Business Intelligence Network. * Long overdue comprehensive coverage of the implementation of technology and tools that enable the new generation of the DW: metadata, temporal data, ETL, unstructured data, and data quality control.

Data Warehousing In The Age Of Big Data

Author: Krish Krishnan
Publisher: Newnes
ISBN: 0124059201
Size: 40.41 MB
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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

Data Warehousing And Business Intelligence For E Commerce

Author: Alan R. Simon
Publisher: Elsevier
ISBN: 9780080491028
Size: 48.65 MB
Format: PDF, ePub, Mobi
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You go online to buy a digital camera. Soon, you realize you've bought a more expensive camera than intended, along with extra batteries, charger, and graphics software-all at the prompting of the retailer. Happy with your purchases? The retailer certainly is, and if you are too, you both can be said to be the beneficiaries of "customer intimacy" achieved through the transformation of data collected during this visit or stored from previous visits into real business intelligence that can be exercised in real time. Data Warehousing and Business Intelligence for e-Commerce is a practical exploration of the technological innovations through which traditional data warehousing is brought to bear on this and other less modest e-commerce applications, such as those at work in B2B, G2C, B2G, and B2E models. The authors examine the core technologies and commercial products in use today, providing a nuts-and-bolts understanding of how you can deploy customer and product data in ways that meet the unique requirements of the online marketplace-particularly if you are part of a brick-and-mortar company with specific online aspirations. In so doing, they build a powerful case for investment in and aggressive development of these approaches, which are likely to separate winners from losers as e-commerce grows and matures. * Includes the latest from successful data warehousing consultants whose work has encouraged the field's new focus on e-commerce. * Presents information that is written for both consultants and practitioners in companies of all sizes. * Emphasizes the special needs and opportunities of traditional brick-and-mortar businesses that are going online or participating in B2B supply chains or e-marketplaces. * Explains how long-standing assumptions about data warehousing have to be rethought in light of emerging business models that depend on customer intimacy. * Provides advice on maintaining data quality and integrity in environments marked by extensive customer self-input. * Advocates careful planning that will help both old economy and new economy companies develop long-lived and successful e-commerce strategies. * Focuses on data warehousing for emerging e-commerce areas such as e-government and B2E environments.

Survey On Intelligent Data Repository Using Soft Computing

Author: A. Prema
Publisher: Infinite Study
ISBN:
Size: 74.21 MB
Format: PDF, ePub
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Data warehouse is one of the components of the overall business intelligence system. An enterprise has one data warehouse, and data marts source has their information from the data warehouse. The Data warehouse is a corporation of all data marts within the enterprise. Information is always accumulated in the dimensional model. In this paper, an intelligent data repository with soft computing is presented. It covers similarity metrics that are commonly used to improve the efficiency of data storages. It also covers multiple decision making methodologies to improve the efficiency of decision making.

Data Virtualization For Business Intelligence Systems

Author: Rick F. van der Lans
Publisher: Elsevier
ISBN: 0123944252
Size: 13.45 MB
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Annotation In this book, Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects.

Data Virtualization For Business Intelligence Systems

Author: Rick van der Lans
Publisher: Elsevier
ISBN: 0123978173
Size: 24.30 MB
Format: PDF, ePub, Docs
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Data virtualization can help you accomplish your goals with more flexibility and agility. Learn what it is and how and why it should be used with Data Virtualization for Business Intelligence Systems. In this book, expert author Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects. You’ll learn the difference is between this new form of data integration and older forms, such as ETL and replication, and gain a clear understanding of how data virtualization really works. Data Virtualization for Business Intelligence Systems outlines the advantages and disadvantages of data virtualization and illustrates how data virtualization should be applied in data warehouse environments. You’ll come away with a comprehensive understanding of how data virtualization will make data warehouse environments more flexible and how it make developing operational BI applications easier. Van der Lans also describes the relationship between data virtualization and related topics, such as master data management, governance, and information management, so you come away with a big-picture understanding as well as all the practical know-how you need to virtualize your data. First independent book on data virtualization that explains in a product-independent way how data virtualization technology works. Illustrates concepts using examples developed with commercially available products. Shows you how to solve common data integration challenges such as data quality, system interference, and overall performance by following practical guidelines on using data virtualization. Apply data virtualization right away with three chapters full of practical implementation guidance. Understand the big picture of data virtualization and its relationship with data governance and information management.

Service Research And Innovation

Author: Amin Beheshti
Publisher: Springer
ISBN: 3319765876
Size: 11.75 MB
Format: PDF, ePub, Docs
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This book constitutes revised selected papers from the Australasian Symposium on Service Research and Innovation, ASSRI, held in Sydney Australia.The 11 full papers presented from ASSRI 2017, which took place during October 19-20, 2017, were carefully reviewed and selected from 26 submissions. The volume also contains 3 papers from ASSRI 2015, which took place during November 2-3, 2015, and one invited paper on the software development processes.The papers were organized in topical sections named: invited talk; modelling; design; quality; social, and application.

Data Model Patterns A Metadata Map

Author: David C. Hay
Publisher: Elsevier
ISBN: 9780080477039
Size: 19.12 MB
Format: PDF, ePub
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Data Model Patterns: A Metadata Map not only presents a conceptual model of a metadata repository but also demonstrates a true enterprise data model of the information technology industry itself. It provides a step-by-step description of the model and is organized so that different readers can benefit from different parts. It offers a view of the world being addressed by all the techniques, methods, and tools of the information processing industry (for example, object-oriented design, CASE, business process re-engineering, etc.) and presents several concepts that need to be addressed by such tools. This book is pertinent, with companies and government agencies realizing that the data they use represent a significant corporate resource recognize the need to integrate data that has traditionally only been available from disparate sources. An important component of this integration is management of the "metadata" that describe, catalogue, and provide access to the various forms of underlying business data. The "metadata repository" is essential to keep track of the various physical components of these systems and their semantics. The book is ideal for data management professionals, data modeling and design professionals, and data warehouse and database repository designers. A comprehensive work based on the Zachman Framework for information architecture—encompassing the Business Owner's, Architect's, and Designer's views, for all columns (data, activities, locations, people, timing, and motivation) Provides a step-by-step description of model and is organized so that different readers can benefit from different parts Provides a view of the world being addressed by all the techniques, methods and tools of the information processing industry (for example, object-oriented design, CASE, business process re-engineering, etc.) Presents many concepts that are not currently being addressed by such tools — and should be

Social Data Analytics

Author: Krish Krishnan
Publisher: Newnes
ISBN: 0123977800
Size: 49.35 MB
Format: PDF, ePub, Mobi
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Social Data Analytics is the first practical guide for professionals who want to employ social data for analytics and business intelligence (BI). This book provides a comprehensive overview of the technologies and platforms and shows you how to access and analyze the data. You'll explore the five major types of social data and learn from cases and platform examples to help you make the most of sentiment, behavioral, social graph, location, and rich media data. A four-step approach to the social BI process will help you access, evaluate, collaborate, and share social data with ease. You'll learn everything you need to know to monitor social media and get an overview of the leading vendors in a crowded space of BI applications. By the end of this book, you will be well prepared for your organization’s next social data analytics project. Provides foundational understanding of new and emerging technologies—social data, collaboration, big data, advanced analytics Includes case studies and practical examples of success and failures Will prepare you to lead projects and advance initiatives that will benefit you and your organization

Decision Support Systems For Business Intelligence

Author: Vicki L. Sauter
Publisher: John Wiley & Sons
ISBN: 1118627237
Size: 35.84 MB
Format: PDF, Mobi
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Praise for the First Edition "This is the most usable decision support systems text. [i]t is far better than any other text in the field" —Computing Reviews Computer-based systems known as decision support systems (DSS) play a vital role in helping professionals across various fields of practice understand what information is needed, when it is needed, and in what form in order to make smart and valuable business decisions. Providing a unique combination of theory, applications, and technology, Decision Support Systems for Business Intelligence, Second Edition supplies readers with the hands-on approach that is needed to understand the implications of theory to DSS design as well as the skills needed to construct a DSS. This new edition reflects numerous advances in the field as well as the latest related technological developments. By addressing all topics on three levels—general theory, implications for DSS design, and code development—the author presents an integrated analysis of what every DSS designer needs to know. This Second Edition features: Expanded coverage of data mining with new examples Newly added discussion of business intelligence and transnational corporations Discussion of the increased capabilities of databases and the significant growth of user interfaces and models Emphasis on analytics to encourage DSS builders to utilize sufficient modeling support in their systems A thoroughly updated section on data warehousing including architecture, data adjustment, and data scrubbing Explanations and implications of DSS differences across cultures and the challenges associated with transnational systems Each chapter discusses various aspects of DSS that exist in real-world applications, and one main example of a DSS to facilitate car purchases is used throughout the entire book. Screenshots from JavaScript® and Adobe® ColdFusion are presented to demonstrate the use of popular software packages that carry out the discussed techniques, and a related Web site houses all of the book's figures along with demo versions of decision support packages, additional examples, and links to developments in the field. Decision Support Systems for Business Intelligence, Second Edition is an excellent book for courses on information systems, decision support systems, and data mining at the advanced undergraduate and graduate levels. It also serves as a practical reference for professionals working in the fields of business, statistics, engineering, and computer technology.