Data Mapping for Data Warehouse Design

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.

Covers all stages of data warehousing and the role of data mapping in eachIncludes a data mapping strategy and techniques that can be applied to many situationsBased on the author’s years of real-world experience designing solutions

1. Introduction
2. Data Mapping Stages
3. Data Mapping Types
4. Data Models
5. Data Mapper's Strategy and Focus
6. Uniqueness of Attributes and Its Importance
7. Pre-Requisites of Data Mapping
8. Surrogate Keys Vs. Natural Keys
9. Data Mapping Document Format
10. Data Analysis Techniques
11. Data Quality
12. Data Mapping Scenarios