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Record Nr. |
UNINA9910824342703321 |
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Autore |
Kimball Ralph |
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Titolo |
The data warehouse toolkit : the definitive guide to dimensional modeling / / Ralph Kimball, Margy Ross |
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Pubbl/distr/stampa |
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Indianapolis, Ind. : , : Wiley, , [2013] |
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©2013 |
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ISBN |
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1-118-73228-6 |
1-118-53077-2 |
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Edizione |
[Third edition] |
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Descrizione fisica |
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1 online resource (601 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Gestor de dades |
Empreses - Informàtica |
Data warehousing |
Business enterprises - Data processing |
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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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Nota di contenuto |
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Cover; Title Page; Copyright; Contents; 1 Data Warehousing, Business Intelligence, and Dimensional Modeling Primer; Different Worlds of Data Capture and Data Analysis; Goals of Data Warehousing and Business Intelligence; Publishing Metaphor for DW/BI Managers; Dimensional Modeling Introduction; Star Schemas Versus OLAP Cubes; Fact Tables for Measurements; Dimension Tables for Descriptive Context; Facts and Dimensions Joined in a Star Schema; Kimball's DW/BI Architecture; Operational Source Systems; Extract, Transformation, and Load System; Presentation Area to Support Business Intelligence |
Business Intelligence ApplicationsRestaurant Metaphor for the Kimball Architecture; Alternative DW/BI Architectures; Independent Data Mart Architecture; Hub-and-Spoke Corporate Information Factory Inmon Architecture; Hybrid Hub-and-Spoke and Kimball Architecture; Dimensional Modeling Myths; Myth 1: Dimensional Models are Only for Summary Data; Myth 2: Dimensional Models are Departmental, Not Enterprise; Myth 3: Dimensional Models are Not Scalable; Myth 4: Dimensional Models are Only for Predictable Usage; Myth 5: |
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Dimensional Models Can't Be Integrated; More Reasons to Think Dimensionally |
Agile ConsiderationsSummary; 2 Kimball Dimensional Modeling Techniques Overview; Fundamental Concepts; Gather Business Requirements and Data Realities; Collaborative Dimensional Modeling Workshops; Four-Step Dimensional Design Process; Business Processes; Grain; Dimensions for Descriptive Context; Facts for Measurements; Star Schemas and OLAP Cubes; Graceful Extensions to Dimensional Models; Basic Fact Table Techniques; Fact Table Structure; Additive, Semi-Additive, Non-Additive Facts; Nulls in Fact Tables; Conformed Facts; Transaction Fact Tables; Periodic Snapshot Fact Tables |
Accumulating Snapshot Fact TablesFactless Fact Tables; Aggregate Fact Tables or OLAP Cubes; Consolidated Fact Tables; Basic Dimension Table Techniques; Dimension Table Structure; Dimension Surrogate Keys; Natural, Durable, and Supernatural Keys; Drilling Down; Degenerate Dimensions; Denormalized Flattened Dimensions; Multiple Hierarchies in Dimensions; Flags and Indicators as Textual Attributes; Null Attributes in Dimensions; Calendar Date Dimensions; Role-Playing Dimensions; Junk Dimensions; Snowflaked Dimensions; Outrigger Dimensions; Integration via Conformed Dimensions |
Conformed DimensionsShrunken Dimensions; Drilling Across; Value Chain; Enterprise Data Warehouse Bus Architecture; Enterprise Data Warehouse Bus Matrix; Detailed Implementation Bus Matrix; Opportunity/Stakeholder Matrix; Dealing with Slowly Changing Dimension Attributes; Type 0: Retain Original; Type 1: Overwrite; Type 2: Add New Row; Type 3: Add New Attribute; Type 4: Add Mini-Dimension; Type 5: Add Mini-Dimension and Type 1 Outrigger; Type 6: Add Type 1 Attributes to Type 2 Dimension; Type 7: Dual Type 1 and Type 2 Dimensions; Dealing with Dimension Hierarchies |
Fixed Depth Positional Hierarchies |
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Sommario/riassunto |
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Updated new edition of Ralph Kimball's groundbreaking book on dimensional modeling for data warehousing and business intelligence! The first edition of Ralph Kimball's The Data Warehouse Toolkit introduced the industry to dimensional modeling, and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds two new chapters on ETL techniques, includes new an |
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