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The data warehouse toolkit [[electronic resource] ] : the definitive guide to dimensional modeling / / Ralph Kimball, Margy Ross
| The data warehouse toolkit [[electronic resource] ] : the definitive guide to dimensional modeling / / Ralph Kimball, Margy Ross |
| Autore | Kimball Ralph |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Indianapolis, Ind., : Wiley, c2013 |
| Descrizione fisica | 1 online resource (601 p.) |
| Disciplina | 658.40380285574 |
| Altri autori (Persone) | RossMargy |
| Soggetto topico |
Data warehousing
Business enterprises - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-118-73228-6
1-118-53077-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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: 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 |
| Record Nr. | UNINA-9910452802803321 |
Kimball Ralph
|
||
| Indianapolis, Ind., : Wiley, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The data warehouse toolkit : the definitive guide to dimensional modeling / / Ralph Kimball, Margy Ross
| The data warehouse toolkit : the definitive guide to dimensional modeling / / Ralph Kimball, Margy Ross |
| Autore | Kimball Ralph |
| Edizione | [Third edition] |
| Pubbl/distr/stampa | Indianapolis, Ind. : , : Wiley, , [2013] |
| Descrizione fisica | 1 online resource (601 p.) |
| Disciplina | 658.40380285574 |
| Altri autori (Persone) | RossMargy |
| Soggetto topico |
Gestor de dades
Empreses - Informàtica Data warehousing Business enterprises - Data processing |
| ISBN |
1-118-73228-6
1-118-53077-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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: 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 |
| Record Nr. | UNINA-9910779708303321 |
|
Kimball Ralph
|
||
| Indianapolis, Ind. : , : Wiley, , [2013] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The data warehouse toolkit : the definitive guide to dimensional modeling / / Ralph Kimball, Margy Ross
| The data warehouse toolkit : the definitive guide to dimensional modeling / / Ralph Kimball, Margy Ross |
| Autore | Kimball Ralph |
| Edizione | [Third edition] |
| Pubbl/distr/stampa | Indianapolis, Ind. : , : Wiley, , [2013] |
| Descrizione fisica | 1 online resource (601 p.) |
| Disciplina | 658.40380285574 |
| Altri autori (Persone) | RossMargy |
| Soggetto topico |
Gestor de dades
Empreses - Informàtica Data warehousing Business enterprises - Data processing |
| ISBN |
1-118-73228-6
1-118-53077-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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: 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 |
| Record Nr. | UNINA-9910824342703321 |
|
Kimball Ralph
|
||
| Indianapolis, Ind. : , : Wiley, , [2013] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||