DW 2.0: The Architecture for the Next Generation of Data Warehousing

Author: W.H. Inmon,Derek Strauss,Genia Neushloss

Publisher: Elsevier

ISBN: 9780080558332

Category: Computers

Page: 400

View: 6880


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.

The Data and Analytics Playbook

Proven Methods for Governed Data and Analytic Quality

Author: Lowell Fryman,Gregory Lampshire,Dan Meers

Publisher: Morgan Kaufmann

ISBN: 0128025476

Category: Computers

Page: 292

View: 3499


The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization. Provides a mature and proven playbook approach (methodology) to enabling data governance that supports agile implementation Features specific examples of current industry challenges in enterprise risk management, including anti-money laundering and fraud prevention Describes business benefit measures and funding approaches using exposure based cost models that augment risk models for cost avoidance analysis and accelerated delivery approaches using data integration sprints for application, integration, and information delivery success

Survey on Intelligent Data Repository Using Soft Computing

Author: A. Prema ,A.Pethalakshmi

Publisher: Infinite Study



Page: 20

View: 1726


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.

Encyclopedia of Information Science and Technology, Third Edition

Author: Khosrow-Pour, Mehdi

Publisher: IGI Global

ISBN: 1466658894

Category: Computers

Page: 10384

View: 8474


"This 10-volume compilation of authoritative, research-based articles contributed by thousands of researchers and experts from all over the world emphasized modern issues and the presentation of potential opportunities, prospective solutions, and future directions in the field of information science and technology"--Provided by publisher.

Data Virtualization for Business Intelligence Systems

Revolutionizing Data Integration for Data Warehouses

Author: Rick van der Lans

Publisher: Elsevier

ISBN: 0123978173

Category: Computers

Page: 296

View: 4601


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.

Data Warehousing 2000

Author: Reinhard Jung,Robert Winter

Publisher: Birkhäuser

ISBN: 9783790813562

Category: Data warehousing

Page: 393

View: 6847


Data Warehousing hat in den letzten Jahren in vielen Unternehmen stark an Bedeutung gewonnen und ist dabei zu einer der zentralen Herausforderungen im Informationsmanagement geworden. FA1/4r viele Anwendungen, wie beispielsweise Customer-Relationship-Management oder FA1/4hrungsinformationssysteme, bilden Data-Warehouse-Architekturen eine wesentliche Grundlage. Der Tagungsband zur Konferenz "Data Warehousing 2000 - Methoden, Anwendungen, Strategien" gibt einen Aoeberblick zum State-of-the-Art sowohl im Bereich Entwicklung aus technischer und organisatorischer bzw. betriebswirtschaftlicher Sicht als auch im Bereich der vielfAltigen AnwendungsmAglichkeiten einer Data-Warehouse-Architektur. Neben AufsAtzen aus dem wissenschaftlichen Bereich finden sich auch Berichte aus laufenden und abgeschlossenen Projekten im Umfeld des Data Warehousing.