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Data Warehousing and Analytics Fueling the Data Engine

Title
Data Warehousing and Analytics [electronic resource] : Fueling the Data Engine / by David Taniar, Wenny Rahayu.
ISBN
9783030819798
Edition
1st ed. 2021.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2021.
Physical Description
1 online resource (XVIII, 435 p.) 381 illus., 262 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This textbook covers all central activities of data warehousing and analytics, including transformation, preparation, aggregation, integration, and analysis. It discusses the full spectrum of the journey of data from operational/transactional databases, to data warehouses and data analytics; as well as the role that data warehousing plays in the data processing lifecycle. It also explains in detail how data warehouses may be used by data engines, such as BI tools and analytics algorithms to produce reports, dashboards, patterns, and other useful information and knowledge. The book is divided into six parts, ranging from the basics of data warehouse design (Part I - Star Schema, Part II - Snowflake and Bridge Tables, Part III - Advanced Dimensions, and Part IV - Multi-Fact and Multi-Input), to more advanced data warehousing concepts (Part V - Data Warehousing and Evolution) and data analytics (Part VI - OLAP, BI, and Analytics). This textbook approaches data warehousing from the case study angle. Each chapter presents one or more case studies to thoroughly explain the concepts and has different levels of difficulty, hence learning is incremental. In addition, every chapter has also a section on further readings which give pointers and references to research papers related to the chapter. All these features make the book ideally suited for either introductory courses on data warehousing and data analytics, or even for self-studies by professionals. The book is accompanied by a web page that includes all the used datasets and codes as well as slides and solutions to exercises.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
February 10, 2022
Series
Data-Centric Systems and Applications,
Data-Centric Systems and Applications,
Contents
1. Introduction
Part I: Star Schema
2. Simple Star Schemas
3. Creating Facts and Dimensions: More Complex Processes
Part II: Snowflake and Bridge Tables
4. Hierarchies
5. Bridge Tables
6. Temporal Data Warehousing
Part III: Advanced Dimension
7. Determinant Dimensions
8. Junk Dimensions
9. Dimension Keys
10. One-Attribute Dimensions
Part IV: Multi-Fact and Multi-Input
11. Multi-Fact Star Schemas
12. Slicing a Fact
13. Multi-Input Operational Databases
Part V: Data Warehousing Granularity and Evolution
14. Data Warehousing Granularity and Levels of Aggregation
15. Designing Lowest-Level Star Schemas
16. Levels of Aggregation: Adding and Removing Dimensions
17. Levels of Aggregation and Bridge Tables
18. Active Data Warehousing
Part VI: OLAP, Business Intelligence, and Data Analytics
19. Online Analytical Processing (OLAP)
20. Pre- and Post-Data Warehousing
21. Data Analytics for Data Warehousing.
Also listed under
Rahayu, Wenny. author.
SpringerLink (Online service)
Citation

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