TY -
GEN
AU - Kimball, Ralph
AU - Ross, Margy
TI -
The data warehouse toolkit
the definitive guide to dimensional modeling
ET - 3. ed.
PB - Wiley
SN - 1118530802
SN - 9781299731844
SN - 1299731848
SN - 9781118732281
SN - 9781118732199
SN - 9781118530771
SN - 9781118530801
KW - Business intelligence
KW - Database design
KW - Business enterprises Data processing Electronic books
KW - Business enterprises Data processing
KW - Data warehousing
KW - Business enterprises
KW - Multidimensional databases
KW - Business enterprises ; Data processing
KW - Electronic books
KW - Business enterprises / Data processing
KW - Business enterprises -- Data processing
KW - Multidimensional databases -- Design
KW - Data processing
KW - Data-Warehouse-Konzept
PY - 2013
N2 - 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
N2 - 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
N2 - 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
N2 - 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
N2 - 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
N2 - Fixed Depth Positional Hierarchies
CY - Indianapolis, Ind.
UR - http://slubdd.de/katalog?TN_libero_mab2
ER -