Data warehousing in the age of big data / (Record no. 3355)

MARC details
000 -LEADER
fixed length control field 03533cam a2200337 i 4500
001 - CONTROL NUMBER
control field 17695534
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20210930193256.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130412s2013 ne a b 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2013004151
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780124058910 (pbk.)
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Transcribing agency DLC
Description conventions rda
Modifying agency DLC
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.D37
Item number K75 2013
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74/5
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Krishnan, Krish.
245 10 - TITLE STATEMENT
Title Data warehousing in the age of big data /
Statement of responsibility, etc. Krish Krishnan.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Amsterdam :
Name of producer, publisher, distributor, manufacturer Morgan Kaufmann is an imprint of Elsevier,
Date of production, publication, distribution, manufacture, or copyright notice 2013.
300 ## - PHYSICAL DESCRIPTION
Extent xxiii, 346 pages :
Other physical details illustrations ;
Dimensions 24 cm
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note Machine generated contents note: Part 1 - Big Data Chapter 1 - Introduction to Big Data Chapter 2 - Complexity of Big Data Chapter 3 - Big Data Processing Architectures Chapter 4 - Big Data Technologies Chapter 5 - Big Data Business Value Part 2 - The Data Warehouse Chapter 6 - Data Warehouse Chapter 7 - Re-Engineering the Data Warehouse Chapter 8 -Workload Management in the Data Warehouse Chapter 9 - New Technology Approaches Part 3 - Extending Big Data into the Data Warehouse Chapter 10 - Integration of Big Data and Data Warehouse Chapter 11 - Data Driven Architecture Chapter 12 - Information Management and Lifecycle Chapter 13 - Big Data Analytics, Visualization and Data Scientist Chapter 14 - Implementing The "Big Data" Data Warehouse Appendix A - Customer Case Studies From Vendors Appendix B - Building The HealthCare Information Factory .
520 ## - SUMMARY, ETC.
Summary, etc. "In conclusion as you come to the end of this book, the concept of a Data Warehouse and its primary goal of serving the enterprise version of truth, and being the single platform for all the source of information will continue to remain intact and valid for many years to come. As we have discussed across many chapters and in many case studies, the limitations that existed with the infrastructures to create, manage and deploy Data Warehouses have been largely eliminated with the availability of Big Data technologies and infrastructure platforms, making the goal of the single version of truth a feasible reality. Integrating and extending Big Data into the Data Warehouse, and creating a larger decision support platform will benefit businesses for years to come. This book has touched upon governance and information lifecycle management aspects of Big Data in the larger program, however you can reuse all the current program management techniques that you follow for the Data Warehouse for this program and even implement agile approaches to integrating and managing data in the Data Warehouse. Technologies will continue to evolve in this spectrum and there will be more additions of solutions, which can be integrated if you follow the modular integration approaches to building and managing the Data Warehouse. The Appendix sections contain many more case studies and a special section on Healthcare Information Factory based on Big Data approaches. These are more guiding posts to help you align your thoughts and goals to building and integrating Big Data in your Data Warehouse"--
Assigning source Provided by publisher.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data warehousing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Big data.
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Library of Congress Classification     Kwara State University Library Kwara State University Library   2017-01-10   QA76.9.D37 .K75 2013 015892-01 2017-01-10 2017-01-10 Books
    Library of Congress Classification     Kwara State University Library Kwara State University Library   2017-01-10   QA76.9.D37 .K75 2013 015892-02 2017-01-10 2017-01-10 Books
    Library of Congress Classification     Kwara State University Library Kwara State University Library   2017-01-10   QA76.9.D37 .K75 2013 015892-03 2017-01-10 2017-01-10 Books