Database and data warehousing technologies / edited by Jovan Pehcevski.

Contributor(s):

Pehcevski, Jovan, editor

Material type:

TextPublication details: Oakville, Ontario : Arcler Press, c2018.Description: xxviii, 281pages : color illustrationsContent type:

text

Media type:

computer

Carrier type:

online resource

Subject(s):

LOC classification:

EBOP QA 76.9 D37 2018

Contents:

Section I: Data Warehouse Technology Chapter 1: Data Warehouse Technology Data Warehouse Design Using Process-Oriented Requirement Analysis Chapter 2: Identification of Categorical Registration Data of Domain Names in Data Warehouse Construction Task Chapter 3: Comparative Study of Data Warehouse Design Approaches Chapter 4: Using Metadata Analysis and Base Analysis Techniques in Data Qualities Framework for Data Warehouses Chapter 5: The Critical Factors Influencing the Adoptions of Data Warehouse Section II: Business-Oriented Data Warehouse Applications Chapter 6: Data Warehousing, Data Mining, OLAP and OLTP Technologies Chapter 7: A Data Warehouse Design for the Detection of Fraud in the Supply Chain by Using the Benford’s Law Chapter 8: Data Load Manifestation in Process Chains in Sap Business Warehouse Chapter 9: Big Data Usage in the Marketing Information System Section III: Bio-Medical Data Warehouse Use Cases Chapter 10: Building a Health Care Data Warehouse Chapter 11: Osteoporosis Data Warehouse in the Osteoporosis Community Health Information Management System Chapter 12: Integrative Genomic and Proteomic Data Warehouse Chapter 13: Truncatulix – A Data Warehouse for the Legume Community Chapter 14: Approaches to Access Biological Data Sources Section IV: Data Warehouse Applications in the Public Sector Chapter 15: Data Warehouse and the Deployment of Data Mining Process to Make Decision for Leishmaniasis in Marrakech City Chapter 16: Data Warehouse Technology and Application in Data Centre Design for E-Government Chapter 17: Data Warehouse Use Geographic Information System for Ornamentals Chapter 18: Gossip Management at Universities Using Big Data Warehouse Model Integrated with a Decision Support System

Summary: A database is an organized collection of data. It is the collection of schemas, tables, queries, reports, views and other objects. A data warehouse is a subject-oriented, integrated, timevariant and non-volatile collection of data in support of management’s decision making process. This book provides a comprehensive compilation of knowledge covering state-ofthe- art developments and research, as well as current innovative activities in data warehousing.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	E-Books	Cavite State University - CCAT Campus		Electronic Resources	ER	EBOP QA 76.9.D37 D38 2018 (Browse shelf(Opens below))				1 copy	Available			EBOP0000043

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Includes references and index.

Section I: Data Warehouse Technology
Chapter 1: Data Warehouse Technology Data Warehouse Design Using Process-Oriented Requirement Analysis
Chapter 2: Identification of Categorical Registration Data of Domain Names in Data Warehouse Construction Task
Chapter 3: Comparative Study of Data Warehouse Design Approaches
Chapter 4: Using Metadata Analysis and Base Analysis Techniques in Data Qualities Framework for Data Warehouses
Chapter 5: The Critical Factors Influencing the Adoptions of Data Warehouse
Section II: Business-Oriented Data Warehouse Applications
Chapter 6: Data Warehousing, Data Mining, OLAP and OLTP Technologies
Chapter 7: A Data Warehouse Design for the Detection of Fraud in the Supply Chain by Using the Benford’s Law
Chapter 8: Data Load Manifestation in Process Chains in Sap Business Warehouse
Chapter 9: Big Data Usage in the Marketing Information System
Section III: Bio-Medical Data Warehouse Use Cases
Chapter 10: Building a Health Care Data Warehouse
Chapter 11: Osteoporosis Data Warehouse in the Osteoporosis Community Health Information Management System
Chapter 12: Integrative Genomic and Proteomic Data Warehouse
Chapter 13: Truncatulix – A Data Warehouse for the Legume Community
Chapter 14: Approaches to Access Biological Data Sources
Section IV: Data Warehouse Applications in the Public Sector
Chapter 15: Data Warehouse and the Deployment of Data Mining Process to Make Decision for Leishmaniasis in Marrakech City
Chapter 16: Data Warehouse Technology and Application in Data Centre Design for E-Government
Chapter 17: Data Warehouse Use Geographic Information System for Ornamentals
Chapter 18: Gossip Management at Universities Using Big Data Warehouse Model Integrated with a Decision Support System

A database is an organized collection of data. It is the collection of schemas, tables, queries, reports, views and other objects. A data warehouse is a subject-oriented, integrated, timevariant and non-volatile collection of data in support of management’s decision making process. This book provides a comprehensive compilation of knowledge covering state-ofthe- art developments and research, as well as current innovative activities in data warehousing.

EBOP00043 1

In English text.

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