Data Mapping for Data Warehouse Design

✍ Scribed by Qamar Shahbaz (Auth.)

• Publisher: Morgan Kaufmann
• Year: 2015
• Tongue: English
• Leaves: 169
• Edition: 1st Edition
• Category: Library

✦ Synopsis

Data mapping in a data warehouse is the process of creating a link between two distinct data models’ (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle.

✦ Table of Contents

Content:
Front-matter,Copyright,DedicationEntitled to full textChapter 1 - Introduction, Page 1
Chapter 2 - Data Mapping Stages, Pages 3-4
Chapter 3 - Data Mapping Types, Page 5
Chapter 4 - Data Models, Pages 7-16
Chapter 5 - Data Mapper’s Strategy and Focus, Pages 17-20
Chapter 6 - Uniqueness of Attributes and its Importance, Pages 21-24
Chapter 7 - Prerequisites of Data Mapping, Pages 25-28
Chapter 8 - Surrogate Keys versus Natural Keys, Pages 29-30
Chapter 9 - Data Mapping Document Format, Pages 31-35
Chapter 10 - Data Analysis Techniques, Pages 37-66
Chapter 11 - Data Quality, Pages 67-82
Chapter 12 - Data Mapping Scenarios, Pages 83-165
Glossary and Nomenclature List, Pages 167-168
Bibliography, Page 169

✦ Subjects

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