Data Mapping for Data Warehouse Design
- 1h 55m
- Qamar Shahbaz Ul Haq
- Elsevier Science and Technology Books, Inc.
- 2016
Data mapping in data warehouse lifecycle 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 transform data from one state to another; every stage has its own unique requirements and challenges. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about data mapping/data transformation. The book contains real life scenarios that reader faces and present solutions/standard techniques across various domains. After reading this book, readers will understand the working of data mapping in data warehouse life cycle.
- Covers all stages of data warehousing and the role of data mapping
- Includes data mapping strategies and techniques that can be applied to business use cases
- Based on the author's years of real-world experience designing solutions
About the Author
Qamar shahbaz Ul Haq is expert in field of data warehousing, big data and have designed reporting/analytical applications in various domains. Working across different industries and cultures, Qamar have gained knowledge of Data warehouse design from all aspects of this field. In previous roles he has created solutions ranging from billing systems to semantic design to performance optimization for maximum throughput of data processing.
In this Book
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Introduction
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Data Mapping Stages
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Data Mapping Types
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Data Models
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Data Mapper's Strategy and Focus
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Uniqueness of Attributes and its Importance
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Prerequisites of Data Mapping
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Surrogate Keys versus Natural Keys
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Data Mapping Document Format
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Data Analysis Techniques
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Data Quality
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Data Mapping Scenarios
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Glossary and Nomenclature List
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Bibliography
