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Data warehouse systems : design and implementation / / Alejandro Vaisman and Esteban Zimányi
Data warehouse systems : design and implementation / / Alejandro Vaisman and Esteban Zimányi
Autore Vaisman Alejandro
Edizione [Second edition.]
Pubbl/distr/stampa Berlin, Germany : , : Springer, , [2022]
Descrizione fisica 1 online resource (713 pages)
Disciplina 658.40380285574
Collana Data-centric systems and applications
Soggetto topico Data warehousing
Management information systems
Database management
ISBN 3-662-65167-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNISA-996483163203316
Vaisman Alejandro  
Berlin, Germany : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Data warehouse systems : design and implementation / / Alejandro Vaisman and Esteban Zimányi
Data warehouse systems : design and implementation / / Alejandro Vaisman and Esteban Zimányi
Autore Vaisman Alejandro
Edizione [Second edition.]
Pubbl/distr/stampa Berlin, Germany : , : Springer, , [2022]
Descrizione fisica 1 online resource (713 pages)
Disciplina 658.40380285574
Collana Data-centric systems and applications
Soggetto topico Data warehousing
Management information systems
Database management
ISBN 3-662-65167-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNINA-9910584481803321
Vaisman Alejandro  
Berlin, Germany : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data Warehouse Systems [[electronic resource] ] : Design and Implementation / / by Alejandro Vaisman, Esteban Zimányi
Data Warehouse Systems [[electronic resource] ] : Design and Implementation / / by Alejandro Vaisman, Esteban Zimányi
Autore Vaisman Alejandro
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XVI, 625 p. 133 illus.)
Disciplina 658.40380285574
Collana Data-Centric Systems and Applications
Soggetto topico Database management
Information storage and retrieval
Management information systems
Application software
Database Management
Information Storage and Retrieval
Business IT Infrastructure
Computer Appl. in Administrative Data Processing
ISBN 3-642-54655-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I Fundamental Concepts -- 1 Introduction -- 2 Database Concepts -- 3 Data Warehouse Concepts -- 4 Conceptual Data Warehouse Design -- 5 Logical Data Warehouse Design -- 6 Querying Data Warehouses -- Part II Implementation and Deployment -- 7 Physical Data Warehouse Design -- 8 Extraction, Transformation and Loading -- 9 Data Analytics: Exploiting the Data Warehouse -- 10 A Method for Data Warehouse Design -- Part III Advanced Topics -- 11 Spatial Data Warehouses -- 12 Trajectory Data Warehouses -- 13 New Data Warehouse Technologies -- 14 Data Warehouses and the Semantic Web -- 15 Conclusion.
Record Nr. UNINA-9910298988003321
Vaisman Alejandro  
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui