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Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes
| Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes |
| Autore | Hughes Ralph <1959-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Waltham, MA, : Morgan Kaufmann, 2013 |
| Descrizione fisica | 1 online resource (379 p.) |
| Disciplina | 005.74/5 |
| Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
| ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
| Record Nr. | UNINA-9910785504103321 |
Hughes Ralph <1959->
|
||
| Waltham, MA, : Morgan Kaufmann, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Agile data warehousing project management : business intelligence systems using Scrum / / Ralph Hughes
| Agile data warehousing project management : business intelligence systems using Scrum / / Ralph Hughes |
| Autore | Hughes Ralph <1959-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Waltham, MA, : Morgan Kaufmann, 2013 |
| Descrizione fisica | 1 online resource (379 p.) |
| Disciplina |
005.74/5
005.745 |
| Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
| ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
| Record Nr. | UNINA-9910825750903321 |
|
Hughes Ralph <1959->
|
||
| Waltham, MA, : Morgan Kaufmann, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes
| Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes |
| Autore | Hughes Ralph <1959-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, : Elsevier / MK, 2012 |
| Descrizione fisica | 1 online resource (379 p.) |
| Disciplina | 005.74/5 |
| Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
| Record Nr. | UNINA-9910462367503321 |
|
Hughes Ralph <1959->
|
||
| Amsterdam ; ; Boston, : Elsevier / MK, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Building and scaling SAP business information warehouse on DB2 UDB ESE [[electronic resource] /] / [Chuck Ballard ... et al.]
| Building and scaling SAP business information warehouse on DB2 UDB ESE [[electronic resource] /] / [Chuck Ballard ... et al.] |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | San Jose, CA, : IBM, International Technical Support Organization, 2004 |
| Descrizione fisica | xvi, 380 p. : ill |
| Disciplina | 005.74/5 |
| Altri autori (Persone) | BallardChuck |
| Collana |
IBM redbooks
DB2 information management software |
| Soggetto topico |
Data warehousing
Management information systems Business enterprises - Computer networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910783104203321 |
| San Jose, CA, : IBM, International Technical Support Organization, 2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Building and scaling SAP business information warehouse on DB2 UDB ESE / / [Chuck Ballard ... et al.]
| Building and scaling SAP business information warehouse on DB2 UDB ESE / / [Chuck Ballard ... et al.] |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | San Jose, CA, : IBM, International Technical Support Organization, 2004 |
| Descrizione fisica | xvi, 380 p. : ill |
| Disciplina | 005.74/5 |
| Altri autori (Persone) | BallardChuck |
| Collana |
IBM redbooks
DB2 information management software |
| Soggetto topico |
Data warehousing
Management information systems Business enterprises - Computer networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front cover -- Contents -- Notices -- Trademarks -- Preface -- The team that wrote this redbook -- Become a published author -- Comments welcome -- Introduction -- Management summary -- Structure of the redbook -- Chapter 1. SAP Business Information Warehouse (BW) -- 1.1 Data warehousing -- 1.1.1 Informational databases -- 1.1.2 Data warehousing -- 1.2 SAP BW positioning -- 1.3 SAP business solutions -- 1.4 SAP NetWeaver -- 1.5 SAP Business Intelligence and SAP BW -- 1.6 SAP BW customer scenario -- 1.7 Requirement for scalability -- Chapter 2. SAP BW technical overview -- 2.1 SAP BW information model -- 2.2 Dataflow in SAP BW -- 2.3 Information access -- 2.4 Hierarchies -- 2.5 Extended star schema (InfoCubes) -- 2.6 Dataload into InfoCube -- 2.7 Aggregates -- 2.7.1 Aggregate example -- 2.7.2 Maintaining aggregates -- 2.8 Compression of requests -- 2.9 Operational data store (ODS) -- 2.10 The SAP BW functional components -- 2.11 SAP BW business content -- Chapter 3. DB2 UDB ESE technical overview -- 3.1 The architecture -- 3.2 Functions and components -- 3.2.1 Database objects -- 3.2.2 Concurrency, locking and isolation levels -- 3.2.3 Parallel processing and partitioning -- 3.2.4 Cost-based optimizer -- 3.2.5 Join methods for distributed tables -- 3.2.6 Static and dynamic SQL statements -- 3.2.7 DB2 64-bit -- 3.3 DB2 monitoring and tuning tools -- 3.4 DB2 Version 8: a few highlights -- 3.4.1 Catalog caching -- 3.4.2 RUNSTATS enhancements -- 3.4.3 Multi-dimensional clustering -- 3.4.4 Concurrency features -- 3.4.5 High availability features -- 3.4.6 Connection concentrator -- 3.4.7 Merge statement -- 3.4.8 Multi-FixPak install for UNIX -- Chapter 4. Building SAP BW on DB2 -- 4.1 Value of building SAP BW on DB2 UDB ESE -- 4.1.1 Scalability -- 4.1.2 High performance -- 4.1.3 Ease of administration -- 4.2 Business advantage: the value proposition.
4.2.1 Low TCO -- 4.2.2 Reduced sizing risk and cost -- 4.3 SAP BW on DB2: value details -- 4.3.1 Architecture and features -- 4.3.2 Database layout -- 4.3.3 Parallel processing on multiple database partitions -- 4.3.4 Intra-partition parallelism -- 4.3.5 SAP BW query processing on DB2 -- 4.3.6 Use of distribution statistics for query optimization -- 4.3.7 New features of the DBA Cockpit 6.40 -- Chapter 5. Project test environment -- 5.1 Hardware configuration -- 5.2 Software configuration -- 5.2.1 Operating system -- 5.2.2 Database management system -- 5.2.3 SAP Business Information Warehouse -- 5.2.4 Front-end software -- 5.3 Installation, scaling, and performance test scenarios -- 5.4 SAP BW sample application -- Chapter 6. Implementing SAP BW on DB2 -- 6.1 Sizing SAP BW on DB2 -- 6.2 Implementation approaches -- 6.2.1 The Implementation Assistant -- 6.3 Preinstallation activities -- 6.3.1 Component considerations -- 6.4 Installation planning -- 6.4.1 The SAP Installation Notes -- 6.4.2 The installation checklists -- 6.4.3 System planning and preparation -- 6.5 Installation procedure -- 6.5.1 Installing the IBM DB2 Universal Database -- 6.5.2 Installing the Central Instance -- 6.5.3 Installing the SAP Database Instance -- 6.6 Post-installation activities -- 6.6.1 Additional post-installation activities -- 6.7 Business Information Warehouse definitions -- 6.7.1 BW general settings -- 6.7.2 Installing the SAP Business Content Add-on -- 6.7.3 Installing an additional Dialog Instance -- 6.8 HACMP for high availability -- 6.8.1 High availability and fault tolerance -- 6.8.2 HACMP clusters -- Chapter 7. Administration of SAP BW -- 7.1 Role-based administration -- 7.2 DB2 UDB administration -- 7.3 Periodic activities -- 7.3.1 Storage management -- 7.3.2 Tablespace and container administration -- 7.3.3 The optimizer and runstats. 7.3.4 Tablespace reorganization -- 7.4 Backup and recovery -- 7.4.1 Defining a backup/recovery strategy and policy -- 7.4.2 Managing the DB2 UDB logfiles -- 7.4.3 Performing DB2 UDB backups -- 7.4.4 Database recovery -- 7.5 Authorization to administer SAP BW -- 7.6 Archiving SAP BW data -- Chapter 8. SAP BW performance -- 8.1 The approach -- 8.2 Health check -- 8.2.1 SAP Notes related to performance and system configuration -- 8.2.2 How to keep DB2 database statistics current with SAP BW -- 8.2.3 How to control DB2 log space consumption with SAP BW -- 8.2.4 Recommended configuration parameters -- 8.3 Performance tuning -- 8.3.1 General SAP BW tuning -- 8.3.2 Tuning DB2 UDB ESE -- 8.4 Performance monitoring of SAP BW on DB2 UDB -- 8.4.1 Performance bottlenecks -- 8.4.2 Proactive monitoring -- 8.4.3 Problem analysis and resolution -- Chapter 9. Scaling out the database -- 9.1 Options for installing and scaling the database -- 9.2 Scaling steps -- 9.2.1 Partitioning the database -- 9.2.2 Relocating database containers -- 9.2.3 Moving database partitions to another server -- 9.3 Summary -- Chapter 10. Scalability factors of SAP BW on DB2 UDB ESE -- 10.1 DB2 scalability studies -- 10.2 Performance study for SAP BW on DB2 UDB EEE -- 10.2.1 Hardware environment -- 10.2.2 Scalability of single and multi-user SAP BW queries -- 10.2.3 Scalability of dataload from PSA into InfoCube -- 10.2.4 Summary of scalability test results -- 10.3 SAP Business Warehouse on DB2 UDB Sun Cluster -- 10.3.1 Hardware and software setup -- 10.3.2 Description of tests -- 10.3.3 Results of scalability tests -- 10.4 Performance of partitioned and unpartitioned database -- Appendix A. SQL analysis with SAP BW -- Glossary -- Abbreviations and acronyms -- Related publications -- IBM Redbooks -- Other publications -- Online resources -- How to get IBM Redbooks -- Help from IBM -- Index. Back cover. |
| Record Nr. | UNINA-9910806141903321 |
| San Jose, CA, : IBM, International Technical Support Organization, 2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data virtualization for business intelligence architectures [[electronic resource] ] : revolutionizing data integration for data warehouses / / Rick F. van der Lans
| Data virtualization for business intelligence architectures [[electronic resource] ] : revolutionizing data integration for data warehouses / / Rick F. van der Lans |
| Autore | Lans Rick F. van der |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, : Elsevier/MK, c2012 |
| Descrizione fisica | 1 online resource (296 p.) |
| Disciplina | 005.74/5 |
| Collana | The Morgan Kaufmann Series on Business Intelligence |
| Soggetto topico |
Business intelligence
Data warehousing Management information systems Virtual computer systems |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-60428-3
9786613784971 0-12-397817-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Data Virtualization for Business Intelligence Systems; Copyright Page; Contents; Foreword; Preface; Introduction; Who Should Read This Book?; Prerequisite Knowledge; Terms and Definitions; And Finally ...; About the Author; 1 Introduction to Data Virtualization; 1.1 Introduction; 1.2 The World of Business Intelligence Is Changing; 1.3 Introduction to Virtualization; 1.4 What Is Data Virtualization?; 1.5 Data Virtualization and Related Concepts; 1.5.1 Data Virtualization versus Encapsulation and Information Hiding; 1.5.2 Data Virtualization versus Abstraction
1.5.3 Data Virtualization versus Data Federation1.5.4 Data Virtualization versus Data Integration; 1.5.5 Data Virtualization versus Enterprise Information Integration; 1.6 Definition of Data Virtualization; 1.7 Technical Advantages of Data Virtualization; 1.8 Different Implementations of Data Virtualization; 1.9 Overview of Data Virtualization Servers; 1.10 Open versus Closed Data Virtualization Servers; 1.11 Other Forms of Data Integration; 1.12 The Modules of a Data Virtualization Server; 1.13 The History of Data Virtualization; 1.14 The Sample Database: World Class Movies 1.15 Structure of This Book2 Business Intelligence and Data Warehousing; 2.1 Introduction; 2.2 What Is Business Intelligence?; 2.3 Management Levels and Decision Making; 2.4 Business Intelligence Systems; 2.5 The Data Stores of a Business Intelligence System; 2.5.1 The Data Warehouse; 2.5.2 The Data Marts; 2.5.3 The Data Staging Area; 2.5.4 The Operational Data Store; 2.5.5 The Personal Data Stores; 2.5.6 A Comparison of the Different Types of Data Stores; 2.6 Normalized Schemas, Star Schemas, and Snowflake Schemas; 2.6.1 Normalized Schemas; 2.6.2 Denormalized Schemas; 2.6.3 Star Schemas 2.6.4 Snowflake Schemas2.7 Data Transformation with Extract Transform Load, Extract Load Transform, and Replication; 2.7.1 Extract Transform Load; 2.7.2 Extract Load Transform; 2.7.3 Replication; 2.8 Overview of Business Intelligence Architectures; 2.9 New Forms of Reporting and Analytics; 2.9.1 Operational Reporting and Analytics; 2.9.2 Deep and Big Data Analytics; 2.9.3 Self-Service Reporting and Analytics; 2.9.4 Unrestricted Ad-Hoc Analysis; 2.9.5 360-Degree Reporting; 2.9.6 Exploratory Analysis; 2.9.7 Text-Based Analysis; 2.10 Disadvantages of Classic Business Intelligence Systems 2.11 Summary3 Data Virtualization Server: The Building Blocks; 3.1 Introduction; 3.2 The High-Level Architecture of a Data Virtualization Server; 3.3 Importing Source Tables and Defining Wrappers; 3.4 Defining Virtual Tables and Mappings; 3.5 Examples of Virtual Tables and Mappings; 3.6 Virtual Tables and Data Modeling; 3.7 Nesting Virtual Tables and Shared Specifications; 3.8 Importing Nonrelational Data; 3.8.1 XML and JSON Documents; 3.8.2 Web Services; 3.8.3 Spreadsheets; 3.8.4 NoSQL Databases; 3.8.5 Multidimensional Cubes and MDX; 3.8.6 Semistructured Data; 3.8.7 Unstructured Data 3.9 Publishing Virtual Tables |
| Record Nr. | UNINA-9910462476203321 |
|
Lans Rick F. van der
|
||
| Amsterdam ; ; Boston, : Elsevier/MK, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data virtualization for business intelligence architectures [[electronic resource] ] : revolutionizing data integration for data warehouses / / Rick F. van der Lans
| Data virtualization for business intelligence architectures [[electronic resource] ] : revolutionizing data integration for data warehouses / / Rick F. van der Lans |
| Autore | Lans Rick F. van der |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, : Elsevier/MK, c2012 |
| Descrizione fisica | 1 online resource (296 p.) |
| Disciplina | 005.74/5 |
| Collana | The Morgan Kaufmann Series on Business Intelligence |
| Soggetto topico |
Business intelligence
Data warehousing Management information systems Virtual computer systems |
| ISBN |
1-281-60428-3
9786613784971 0-12-397817-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Data Virtualization for Business Intelligence Systems; Copyright Page; Contents; Foreword; Preface; Introduction; Who Should Read This Book?; Prerequisite Knowledge; Terms and Definitions; And Finally ...; About the Author; 1 Introduction to Data Virtualization; 1.1 Introduction; 1.2 The World of Business Intelligence Is Changing; 1.3 Introduction to Virtualization; 1.4 What Is Data Virtualization?; 1.5 Data Virtualization and Related Concepts; 1.5.1 Data Virtualization versus Encapsulation and Information Hiding; 1.5.2 Data Virtualization versus Abstraction
1.5.3 Data Virtualization versus Data Federation1.5.4 Data Virtualization versus Data Integration; 1.5.5 Data Virtualization versus Enterprise Information Integration; 1.6 Definition of Data Virtualization; 1.7 Technical Advantages of Data Virtualization; 1.8 Different Implementations of Data Virtualization; 1.9 Overview of Data Virtualization Servers; 1.10 Open versus Closed Data Virtualization Servers; 1.11 Other Forms of Data Integration; 1.12 The Modules of a Data Virtualization Server; 1.13 The History of Data Virtualization; 1.14 The Sample Database: World Class Movies 1.15 Structure of This Book2 Business Intelligence and Data Warehousing; 2.1 Introduction; 2.2 What Is Business Intelligence?; 2.3 Management Levels and Decision Making; 2.4 Business Intelligence Systems; 2.5 The Data Stores of a Business Intelligence System; 2.5.1 The Data Warehouse; 2.5.2 The Data Marts; 2.5.3 The Data Staging Area; 2.5.4 The Operational Data Store; 2.5.5 The Personal Data Stores; 2.5.6 A Comparison of the Different Types of Data Stores; 2.6 Normalized Schemas, Star Schemas, and Snowflake Schemas; 2.6.1 Normalized Schemas; 2.6.2 Denormalized Schemas; 2.6.3 Star Schemas 2.6.4 Snowflake Schemas2.7 Data Transformation with Extract Transform Load, Extract Load Transform, and Replication; 2.7.1 Extract Transform Load; 2.7.2 Extract Load Transform; 2.7.3 Replication; 2.8 Overview of Business Intelligence Architectures; 2.9 New Forms of Reporting and Analytics; 2.9.1 Operational Reporting and Analytics; 2.9.2 Deep and Big Data Analytics; 2.9.3 Self-Service Reporting and Analytics; 2.9.4 Unrestricted Ad-Hoc Analysis; 2.9.5 360-Degree Reporting; 2.9.6 Exploratory Analysis; 2.9.7 Text-Based Analysis; 2.10 Disadvantages of Classic Business Intelligence Systems 2.11 Summary3 Data Virtualization Server: The Building Blocks; 3.1 Introduction; 3.2 The High-Level Architecture of a Data Virtualization Server; 3.3 Importing Source Tables and Defining Wrappers; 3.4 Defining Virtual Tables and Mappings; 3.5 Examples of Virtual Tables and Mappings; 3.6 Virtual Tables and Data Modeling; 3.7 Nesting Virtual Tables and Shared Specifications; 3.8 Importing Nonrelational Data; 3.8.1 XML and JSON Documents; 3.8.2 Web Services; 3.8.3 Spreadsheets; 3.8.4 NoSQL Databases; 3.8.5 Multidimensional Cubes and MDX; 3.8.6 Semistructured Data; 3.8.7 Unstructured Data 3.9 Publishing Virtual Tables |
| Record Nr. | UNINA-9910790315203321 |
|
Lans Rick F. van der
|
||
| Amsterdam ; ; Boston, : Elsevier/MK, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data virtualization for business intelligence architectures : revolutionizing data integration for data warehouses / / Rick F. van der Lans
| Data virtualization for business intelligence architectures : revolutionizing data integration for data warehouses / / Rick F. van der Lans |
| Autore | Lans Rick F. van der |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, : Elsevier/MK, c2012 |
| Descrizione fisica | 1 online resource (296 p.) |
| Disciplina |
005.74/5
658.4038011 |
| Collana | The Morgan Kaufmann Series on Business Intelligence |
| Soggetto topico |
Business intelligence
Data warehousing Management information systems Virtual computer systems |
| ISBN |
1-281-60428-3
9786613784971 0-12-397817-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Data Virtualization for Business Intelligence Systems; Copyright Page; Contents; Foreword; Preface; Introduction; Who Should Read This Book?; Prerequisite Knowledge; Terms and Definitions; And Finally ...; About the Author; 1 Introduction to Data Virtualization; 1.1 Introduction; 1.2 The World of Business Intelligence Is Changing; 1.3 Introduction to Virtualization; 1.4 What Is Data Virtualization?; 1.5 Data Virtualization and Related Concepts; 1.5.1 Data Virtualization versus Encapsulation and Information Hiding; 1.5.2 Data Virtualization versus Abstraction
1.5.3 Data Virtualization versus Data Federation1.5.4 Data Virtualization versus Data Integration; 1.5.5 Data Virtualization versus Enterprise Information Integration; 1.6 Definition of Data Virtualization; 1.7 Technical Advantages of Data Virtualization; 1.8 Different Implementations of Data Virtualization; 1.9 Overview of Data Virtualization Servers; 1.10 Open versus Closed Data Virtualization Servers; 1.11 Other Forms of Data Integration; 1.12 The Modules of a Data Virtualization Server; 1.13 The History of Data Virtualization; 1.14 The Sample Database: World Class Movies 1.15 Structure of This Book2 Business Intelligence and Data Warehousing; 2.1 Introduction; 2.2 What Is Business Intelligence?; 2.3 Management Levels and Decision Making; 2.4 Business Intelligence Systems; 2.5 The Data Stores of a Business Intelligence System; 2.5.1 The Data Warehouse; 2.5.2 The Data Marts; 2.5.3 The Data Staging Area; 2.5.4 The Operational Data Store; 2.5.5 The Personal Data Stores; 2.5.6 A Comparison of the Different Types of Data Stores; 2.6 Normalized Schemas, Star Schemas, and Snowflake Schemas; 2.6.1 Normalized Schemas; 2.6.2 Denormalized Schemas; 2.6.3 Star Schemas 2.6.4 Snowflake Schemas2.7 Data Transformation with Extract Transform Load, Extract Load Transform, and Replication; 2.7.1 Extract Transform Load; 2.7.2 Extract Load Transform; 2.7.3 Replication; 2.8 Overview of Business Intelligence Architectures; 2.9 New Forms of Reporting and Analytics; 2.9.1 Operational Reporting and Analytics; 2.9.2 Deep and Big Data Analytics; 2.9.3 Self-Service Reporting and Analytics; 2.9.4 Unrestricted Ad-Hoc Analysis; 2.9.5 360-Degree Reporting; 2.9.6 Exploratory Analysis; 2.9.7 Text-Based Analysis; 2.10 Disadvantages of Classic Business Intelligence Systems 2.11 Summary3 Data Virtualization Server: The Building Blocks; 3.1 Introduction; 3.2 The High-Level Architecture of a Data Virtualization Server; 3.3 Importing Source Tables and Defining Wrappers; 3.4 Defining Virtual Tables and Mappings; 3.5 Examples of Virtual Tables and Mappings; 3.6 Virtual Tables and Data Modeling; 3.7 Nesting Virtual Tables and Shared Specifications; 3.8 Importing Nonrelational Data; 3.8.1 XML and JSON Documents; 3.8.2 Web Services; 3.8.3 Spreadsheets; 3.8.4 NoSQL Databases; 3.8.5 Multidimensional Cubes and MDX; 3.8.6 Semistructured Data; 3.8.7 Unstructured Data 3.9 Publishing Virtual Tables |
| Altri titoli varianti | Revolutionizing data integration for data warehouses |
| Record Nr. | UNINA-9910812146003321 |
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Lans Rick F. van der
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| Amsterdam ; ; Boston, : Elsevier/MK, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Warehousing and Knowledge Discovery [[electronic resource] ] : 13th International Conference, DaWaK 2011, Toulouse, France, August 29- September 2, 2011, Proceedings / / edited by Alfredo Cuzzocrea, Umeshwar Dayal
| Data Warehousing and Knowledge Discovery [[electronic resource] ] : 13th International Conference, DaWaK 2011, Toulouse, France, August 29- September 2, 2011, Proceedings / / edited by Alfredo Cuzzocrea, Umeshwar Dayal |
| Edizione | [1st ed. 2011.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 |
| Descrizione fisica | 1 online resource (XIV, 498 p. 180 illus.) |
| Disciplina | 005.74/5 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Computer communication systems
Management information systems Computer science Data encryption (Computer science) Computers and civilization Application software Algorithms Computer Communication Networks Management of Computing and Information Systems Cryptology Computers and Society Information Systems Applications (incl. Internet) Algorithm Analysis and Problem Complexity |
| ISBN | 3-642-23544-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466064603316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Data warehousing fundamentals for IT professionals / / Paulraj Ponniah
| Data warehousing fundamentals for IT professionals / / Paulraj Ponniah |
| Autore | Ponniah Paulraj |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : John Wiley & Sons, c2010 |
| Descrizione fisica | 1 online resource (601 p.) |
| Disciplina |
005.74/5
005.745 |
| Altri autori (Persone) | PonniahPaulraj |
| Soggetto topico | Data warehousing |
| ISBN |
1-118-21130-8
1-282-70762-0 9786612707629 0-470-60413-1 0-470-60411-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
DATA WAREHOUSING FUNDAMENTALS FOR IT PROFESSIONALS; CONTENTS; PREFACE; PART 1 OVERVIEW AND CONCEPTS; 1 THE COMPELLING NEED FOR DATA WAREHOUSING; 2 DATA WAREHOUSE: THE BUILDING BLOCKS; 3 TRENDS IN DATA WAREHOUSING; PART 2 PLANNING AND REQUIREMENTS; 4 PLANNING AND PROJECT MANAGEMENT; 5 DEFINING THE BUSINESS REQUIREMENTS; 6 REQUIREMENTS AS THE DRIVING FORCE FOR DATA WAREHOUSING; PART 3 ARCHITECTURE AND INFRASTRUCTURE; 7 ARCHITECTURAL COMPONENTS; 8 INFRASTRUCTURE AS THE FOUNDATION FOR DATA WAREHOUSING; 9 THE SIGNIFICANT ROLE OF METADATA; PART 4 DATA DESIGN AND DATA PREPARATION
10 PRINCIPLES OF DIMENSIONAL MODELING11 DIMENSIONAL MODELING: ADVANCED TOPICS; 12 DATA EXTRACTION, TRANSFORMATION, AND LOADING; 13 DATA QUALITY: A KEY TO SUCCESS; PART 5 INFORMATION ACCESS AND DELIVERY; 14 MATCHING INFORMATION TO THE CLASSES OF USERS; 15 OLAP IN THE DATA WAREHOUSE; 16 DATA WAREHOUSING AND THE WEB; 17 DATA MINING BASICS; PART 6 IMPLEMENTATION AND MAINTENANCE; 18 THE PHYSICAL DESIGN PROCESS; 19 DATA WAREHOUSE DEPLOYMENT; 20 GROWTH AND MAINTENANCE; ANSWERS TO SELECTED EXERCISES; APPENDIX A: PROJECT LIFE CYCLE STEPS AND CHECKLISTS; APPENDIX B: CRITICAL FACTORS FOR SUCCESS APPENDIX C: GUIDELINES FOR EVALUATING VENDOR SOLUTIONSAPPENDIX D: HIGHLIGHTS OF VENDORS AND PRODUCTS; APPENDIX E: REAL-WORLD EXAMPLES OF BEST PRACTICES; REFERENCES; GLOSSARY; INDEX |
| Altri titoli varianti | Data warehousing fundamentals for information technology professionals |
| Record Nr. | UNINA-9910140833603321 |
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Ponniah Paulraj
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| Hoboken, N.J., : John Wiley & Sons, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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