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Record Nr. |
UNINA9910783274103321 |
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Autore |
Loshin David <1963-> |
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Titolo |
Business intelligence [[electronic resource] ] : the savvy manager's guide, getting onboard with emerging IT / / David Loshin ; [foreword by Ronald J. Powell] |
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Pubbl/distr/stampa |
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Amsterdam ; ; Boston, : Morgan Kaufmann Publishers, c2003 |
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ISBN |
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1-281-07824-7 |
9786611078249 |
0-08-050054-4 |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (292 p.) |
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Collana |
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The savvy manager's guides |
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Disciplina |
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Soggetti |
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Business intelligence |
Information technology - Management |
Management information systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Front Cover; Business Intelligence; Copyright Page; Contents; Foreword; Preface; Chapter 1. Business Intelligence and Information Exploitation; Why Business Intelligence?; The Information Asset; Exploiting Information; Business Intelligence and Program Success; What Is Business Intelligence?; Actionable Knowledge; Selected Readings; Chapter 2. The Value of Business Intelligence; The Information Asset and Data Valuation; Actionable Knowledge-Return on Investment; Business Intelligence Applications; The Intelligence Dashboard; Business Intelligence Adds Value; Chapter 3. Planning for Success |
Initiating a ProgramBusiness/Information Technology Partnership; Business Intelligence Success Factors; Team Building; Strategic versus Tactical Planning; Summary; Chapter 4. The Business Intelligence Environment; The Business Case; The Business Intelligence Process; System Infrastructure; Information Access, Delivery, and Analysis; Services; Management Issues; Seek to Learn More; Chapter 5. Business Models and Information Flow; The Business Case; Information Processing and Information Flow; The Information Flow Model; Usage in Practice; Modeling Frameworks; Management Issues; Learning More |
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Chapter 6. Data Warehouses, Online Analytical Processing, and MetadataThe Business Case; Data Models; The Data Warehouse; The Data Mart; Online Analytical Processing; Metadata; Management Issues; Summary; Chapter 7. Business Rules; The Business Case; The Business Rules Approach; What Is a Business Rule?; What Is a Business Rule System?; Sources of Business Rules; Management Issues; To Learn More; Chapter 8. Data Profiling; The Business Case; Data Profiling Activities; Data Model Inference; Attribute Analysis; Relationship Analysis; Management Issues; The Last Word |
Chapter 9. Data Quality and Information ComplianceThe Business Case; More Than Just Names and Addresses; Types of Errors; Data Cleansing; Business Rule-Based Information Compliance; Management Issues; To Learn More; Chapter 10. Information Integration; The Business Case; ETL: Extract, Transform, Load; Enterprise Application Integration and Web Services; Record Linkage and Consolidation; Management Issues; To Learn More; Chapter 11. The Value of Parallelism; The Business Case; Parallelism and Granularity; Parallel Processing Systems; Dependence; Parallelism and Business Intelligence |
Management IssuesTo Learn More; Chapter 12. Alternate Information Contexts; The Business Case; Psychographics and Demographics; Geographic Data; Web Behavior Intelligence; Management Issues; To Learn More; Chapter 13. Data Enhancement; The Business Case; Types of Data Enhancement; Incremental Enhancements; Batch Enhancements; Standardization; Example: Address Standardization; Enhancement Methodologies; Management Issues; To Learn More; Chapter 14. Knowledge Discovery and Data Mining; The Business Case; Data Mining and the Data Warehouse; The Virtuous Cycle |
Directed versus Undirected Knowledge Discovery |
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Sommario/riassunto |
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Business Intelligence describes the basic architectural components of a business intelligence environment, ranging from traditional topics such as business process modeling, data modeling, and more modern topics such as business rule systems, data profiling, information compliance and data quality, data warehousing, and data mining. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. The book contains a quick reference gui |
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