Data Warehouse Systems

With this textbook, Vaisman and Zimányi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes "Fundamental Concepts" including multi-dimensional models; conceptual and logical data warehouse design; and MDX, DAX and SQL/OLAP. This part also covers data analytics using Power BI and Analysis Services for producing indicators and dashboards. Subsequently, Part II details "Implementation and Deployment," which includes physical data warehouse design; data extraction, transformation, and loading (ETL); and data warehouse design methodologies. Lastly, Part III covers "Advanced Topics". This part is almost completely new in this second edition and includes chapters with an in-depth coverage of temporal data warehouses as well as graph data warehouses using Neo4j. The chapter on spatial data warehouses includes a detailed coverage of mobility analysis and mobility data warehousing using MobilityDB moving object database. The last chapter covering recent developments in data warehousing includes an extensive study of big data management and the usage of Hadoop, Spark, distributed, in-memory, columnar, NoSQL, and NewSQL database systems, as well as data lakes in the context of analytical data processing.

As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Power BI. All chapters have been revised and updated to the latest versions of the software tools used. For querying, KPIs, and reporting, DAX and Power BI have been added. All examples presented in SQL and MDX in the first edition, are now also developed in DAX. Dashboards are implemented in Power BI and Reporting Services. The chapter on ETL has been expanded for implementing ETL processes in PostgreSQL. Review questions and exercises complement each chapter to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available online and includes electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter.

Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style.