Data warehouse systems : design and implementation / / Alejandro Vaisman and Esteban Zimányi

• Record Nr.: UNISA996483163203316
• Autore: Vaisman Alejandro
• Pubbl/distr/stampa: Berlin, Germany : , : Springer, , [2022]; ©2022
• ISBN: 3-662-65167-X
• Edizione: [Second edition.]
• Descrizione fisica: 1 online resource (713 pages)
• Collana: Data-centric systems and applications
• Disciplina: 658.40380285574
• Soggetti: Data warehousing; Management information systems; Database management
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references (pages 647-665) and index.
• Nota di contenuto: Intro -- Foreword to the Second Edition -- Foreword to the First Edition -- Preface -- Objective of the Book -- Organization of the Book and Teaching Paths -- Acknowledgments -- About the Authors -- Contents -- Part I Fundamental Concepts -- Chapter 1 Introduction -- 1.1 An Overview of Data Warehousing -- 1.2 Emerging Data Warehousing Technologies -- 1.3 Review Questions -- Chapter 2 Database Concepts -- 2.1 Database Design -- 2.2 The Northwind Case Study -- 2.3 Conceptual Database Design -- 2.4 Logical Database Design -- 2.4.1 The Relational Model -- 2.4.2 Normalization -- 2.4.3 Relational Query Languages -- 2.5 Physical Database Design -- 2.6 Summary -- 2.7 Bibliographic Notes -- 2.8 Review Questions -- 2.9 Exercises -- Chapter 3 Data Warehouse Concepts -- 3.1 Multidimensional Model -- 3.1.1 Hierarchies -- 3.1.2 Measures -- 3.2 OLAP Operations -- 3.3 Data Warehouses -- 3.4 Data Warehouse Architecture -- 3.4.1 Back-End Tier -- 3.4.2 Data Warehouse Tier -- 3.4.3 OLAP Tier -- 3.4.4 Front-End Tier -- 3.4.5 Variations of the Architecture -- 3.5 Overview of Microsoft SQL Server BI Tools -- 3.6 Summary -- 3.7 Bibliographic Notes -- 3.8 Review Questions -- 3.9 Exercises -- Chapter 4 Conceptual Data Warehouse Design -- 4.1 Conceptual Modeling of Data Warehouses -- 4.2 Hierarchies -- 4.2.1 Balanced Hierarchies -- 4.2.2 Unbalanced Hierarchies -- 4.2.3 Generalized Hierarchies -- 4.2.4 ; Alternative Hierarchies -- 4.2.5 Parallel Hierarchies -- 4.2.6 Nonstrict Hierarchies -- 4.3 Advanced Modeling Aspects -- 4.3.1 Facts with Multiple Granularities -- 4.3.2 Many-to-Many Dimensions -- 4.3.3 Links between Facts -- 4.4 Querying the Northwind Cube Using the OLAP Operations -- 4.5 Summary -- 4.6 Bibliographic Notes -- 4.7 Review Questions -- 4.8 Exercises -- Chapter 5 Logical Data Warehouse Design -- 5.1 Logical Modeling of Data Warehouses.; 5.2 Relational Data Warehouse Design -- 5.3 Relational Representation of Data Warehouses -- 5.4 Time Dimension -- 5.5 Logical Representation of Hierarchies -- 5.5.1 Balanced Hierarchies -- 5.5.2 Unbalanced Hierarchies -- 5.5.3 Generalized Hierarchies -- 5.5.4 Alternative Hierarchies -- 5.5.5 Parallel Hierarchies -- 5.5.6 Nonstrict Hierarchies -- 5.6 Advanced Modeling Aspects -- 5.6.1 Facts with Multiple Granularities -- 5.6.2 Many-to-Many Dimensions -- 5.6.3 Links between Facts -- 5.7 Slowly Changing Dimensions -- 5.8 Performing OLAP Queries with SQL -- 5.9 Defining the Northwind Data Warehouse in Analysis Services -- 5.9.1 Multidimensional Model -- 5.9.2 Tabular Model -- 5.10 Summary -- 5.11 Bibliographic Notes -- 5.12 Review Questions -- 5.13 Exercises -- Chapter 6 Data Analysis in Data Warehouses -- 6.1 Introduction to MDX -- 6.1.1 Tuples and Sets -- 6.1.2 Basic Queries -- 6.1.3 Slicing -- 6.1.4 Navigation -- 6.1.5 Cross Join -- 6.1.6 Subqueries -- 6.1.7 Calculated Members and Named Sets -- 6.1.8 Relative Navigation -- 6.1.9 Time-Related Calculations -- 6.1.10 Filtering -- 6.1.11 Sorting -- 6.1.12 Top and Bottom Analysis -- 6.1.13 Aggregation Functions -- 6.2 Introduction to DAX -- 6.2.1 Expressions -- 6.2.2 Evaluation Context -- 6.2.3 Queries -- 6.2.4 Filtering -- 6.2.5 Hierarchy Handling -- 6.2.6 Time-Related Calculations -- 6.2.7 Top and Bottom Analysis -- 6.2.8 Table Operations -- 6.3 Key Performance Indicators -- 6.3.1 Classification of Key Performance Indicators -- 6.3.2 Defining Key Performance Indicators -- 6.4 Dashboards -- 6.4.1 Types of Dashboards -- 6.4.2 Guidelines for Dashboard Design -- 6.5 Summary -- 6.6 Bibliographic Notes -- 6.7 Review Questions -- Chapter 7 Data Analysis in the Northwind Data Warehouse -- 7.1 Querying the Multidimensional Model in MDX -- 7.2 Querying the Tabular Model in DAX.; 7.3 Querying the Relational Data Warehouse in SQL -- 7.4 Comparison of MDX, DAX, and SQL -- 7.5 KPIs for the Northwind Case Study -- 7.5.1 KPIs in Analysis Services Multidimensional -- 7.5.2 KPIs in Analysis Services Tabular -- 7.6 Dashboards for the Northwind Case Study -- 7.6.1 Dashboards in Reporting Services -- 7.6.2 Dashboards in Power BI -- 7.7 Summary -- 7.8 Review Questions -- 7.9 Exercises -- Part II Implementation and Deployment -- Chapter 8 Physical Data Warehouse Design -- 8.1 Physical Modeling of Data Warehouses -- 8.2 Materialized Views -- 8.2.1 Algorithms Using Full Information -- 8.2.2 Algorithms Using Partial Information -- 8.3 Data Cube Maintenance -- 8.4 Computation of a Data Cube -- 8.4.1 PipeSort Algorithm -- 8.4.2 Cube Size Estimation -- 8.4.3 Partial Computation of a Data Cube -- 8.5 Indexes for Data Warehouses -- 8.5.1 Bitmap Indexes -- 8.5.2 Bitmap Compression -- 8.5.3 Join Indexes -- 8.6 Evaluation of Star Queries -- 8.7 Partitioning -- 8.8 Parallel Processing -- 8.9 Physical Design in SQL Server and Analysis Services -- 8.9.1 Indexed Views -- 8.9.2 Partition-Aligned Indexed Views -- 8.9.3 Column-Store Indexes -- 8.9.4 Partitions in Analysis Services -- 8.10 Query Performance in Analysis Services -- 8.11 Summary -- 8.12 Bibliographic Notes -- 8.13 Review Questions -- 8.14 Exercises -- Chapter 9 Extraction, Transformation, and Loading -- 9.1 Business Process Modeling Notation -- 9.2 Conceptual ETL Design Using BPMN -- 9.3 Conceptual Design of the Northwind ETL Process -- 9.4 SQL Server Integration ; Services -- 9.5 The Northwind ETL Process in Integration Services -- 9.6 Implementing ETL Processes in SQL -- 9.7 Summary -- 9.8 Bibliographic Notes -- 9.9 Review Questions -- 9.10 Exercises -- Chapter 10 A Method for Data Warehouse Design -- 10.1 Approaches to Data Warehouse Design -- 10.2 General Overview of the Method.; 10.3 Requirements Specification -- 10.3.1 Business-Driven Requirements Specification -- 10.3.2 Data-driven Requirements Specification -- 10.3.3 Business/Data-driven Requirements Specification -- 10.4 Conceptual Design -- 10.4.1 Business-Driven Conceptual Design -- 10.4.2 Data-driven Conceptual Design -- 10.4.3 Business/Data-driven Conceptual Design -- 10.5 Logical Design -- 10.5.1 Logical Schemas -- 10.5.2 ETL Processes -- 10.6 Physical Design -- 10.7 Characterization of the Various Approaches -- 10.7.1 Business-Driven Approach -- 10.7.2 Data-driven Approach -- 10.7.3 Business/Data-driven Approach -- 10.8 Summary -- 10.9 Bibliographic Notes -- 10.10 Review Questions -- 10.11 Exercises -- Part III Advanced Topics -- Chapter 11 Temporal and Multiversion Data Warehouses -- 11.1 Manipulating Temporal Information in SQL -- 11.2 Conceptual Design of Temporal Data Warehouses -- 11.2.1 Time Data Types -- 11.2.2 Synchronization Relationships -- 11.2.3 A Conceptual Model for Temporal Data Warehouses -- 11.2.4 Temporal Hierarchies -- 11.2.5 Temporal Facts -- 11.3 Logical Design of Temporal Data Warehouses -- 11.4 Implementation Considerations -- 11.4.1 Period Encoding -- 11.4.2 Tables for Temporal Roll-Up -- 11.4.3 Integrity Constraints -- 11.4.4 Measure Aggregation -- 11.4.5 Temporal Measures -- 11.5 Querying the Temporal Northwind Data Warehouse in SQL -- 11.6 Temporal Data Warehouses versus Slowly Changing Dimensions -- 11.7 Conceptual Design of Multiversion Data Warehouses -- 11.8 Logical Design of Multiversion Data Warehouses -- 11.9 Querying the Multiversion Northwind Data Warehouse in SQL -- 11.10 Summary -- 11.11 Bibliographic Notes -- 11.12 Review Questions -- 11.13 Exercises -- Chapter 12 Spatial and Mobility Data Warehouses -- 12.1 Conceptual Design of Spatial Data Warehouses -- 12.1.1 Spatial Data Types -- 12.1.2 Topological relationships.; 12.1.3 Continuous Fields -- 12.1.4 A Conceptual Model of Spatial Data Warehouses -- 12.2 Implementation Considerations for Spatial Data -- 12.2.1 Spatial Reference Systems -- 12.2.2 Vector Model -- 12.2.3 Raster Model -- 12.3 Logical Design of Spatial Data Warehouses -- 12.4 Topological Constraints -- 12.5 Querying the GeoNorthwind Data Warehouse in SQL -- 12.6 Mobility Data Analysis -- 12.7 Temporal Types -- 12.8 Temporal Types in MobilityDB -- 12.9 Mobility Data Warehouses -- 12.10 Querying the Northwind Mobility Data Warehouse in SQL -- 12.11 Summary -- 12.12 Bibliographic Notes -- 12.13 Review Questions -- 12.14 Exercises -- Chapter 13 Graph Data Warehouses -- 13.1 Graph Data Models -- 13.2 Property Graph Database Systems -- 13.2.1 Neo4j -- 13.2.2 Introduction to Cypher -- 13.2.3 Querying the Northwind Cube with Cypher -- 13.3 OLAP on Hypergraphs -- 13.3.1 Operations on Hypergraphs -- 13.3.2 OLAP on Trajectory Graphs -- 13.4 Graph Processing Frameworks -- 13.4.1 Gremlin -- 13.4.2 JanusGraph -- 13.5 Bibliographic Notes -- 13.6 Review Questions -- 13.7 Exercises -- Chapter 14 Semantic Web Data Warehouses -- 14.1 Semantic Web -- 14.1.1 Introduction to RDF and RDFS -- 14.1.2 RDF Serializations -- 14.1.3 RDF Representation of Relational Data -- 14.2 Introduction to SPARQL -- 14.2.1 SPARQL Basics -- 14.2.2 SPARQL Semantics -- 14.3 RDF Representation of Multidimensional Data -- 14.4 Representation of the Northwind Cube in QB4OLAP -- 14.5 Querying the Northwind Cube in SPARQL -- 14.6 Summary -- 14.7 Bibliographic Notes -- 14.8 Review Questions -- ; 14.9 Exercises -- Chapter 15 Recent Developments in Big Data Warehouses -- 15.1 Data Warehousing in the Age of Big Data -- 15.2 Distributed Processing Frameworks -- 15.2.1 Hadoop -- 15.2.2 Hive -- 15.2.3 Spark -- 15.2.4 Comparison of Hadoop and Spark -- 15.2.5 Kylin -- 15.3 Distributed Database Systems.; 15.3.1 MySQL Cluster.