Data warehouse design : modern principles and methodologies / Matteo Golfarelli, Stefano Rizzi ; traducción de Claudio Pagliarani.
Tipo de material:
TextoIdioma: Inglés Lenguaje original: Italiano Productor: New York : Distribuidor: McGraw-Hill, Fecha de copyright: ©2009Edición: 1a ediciónDescripción: xxi, 458 páginas : ilustraciones ; 24 x 17 cmTipo de contenido: - texto
- sin medio
- volumen
- 9780071610391
- Data warehouse
- QA 76 .9 .D37 G62 2009
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Biblioteca Antonio Enriquez Savignac | Biblioteca Antonio Enriquez Savignac | COLECCIÓN RESERVA | QA 76 .9 .D37 G62 2009 (Navegar estantería(Abre debajo)) | 1 | No para préstamo | Ingeniería en Datos e Inteligencia Organizacional | 040446 |
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| QA76.9.D35 C1368 2006 Estructuras de datos / | QA 76 .9 .D35 S25 1990 Applications of spatial data structures : computer graphics, image processing, and gis / | QA 76 .9 .D35 S27 Foundations of multidimensional and metric data structures / | QA 76 .9 .D37 G62 2009 Data warehouse design : modern principles and methodologies / | QA 76 .9 .D37 I4575 2015 Data architecture : a primer for the data scientist : big data, data warehouse and data vault / | QA 76 .9 .D37 K53 2004 The data warehouse ETL toolkit : practical techniques for extracting, cleaning, conforming, and delivering data / | QA 76.9.D37 K55 2016 The Kimball Group reader : relentlessly practical tools for data warehousing and business intelligence / |
Incluye bibliografía: páginas 429-443
Introduction to Data Warehousing -- Data Warehouse System Lifecycle -- Analysis and reconciliation of Data Sources -- User requeriments analysis -- Conceptual modeling -- Conceptuaol design -- Workload and data volume -- Logical modeling -- Logical design -- Data-staging design -- Indexes for the Data Warehouse -- Physical design -- Data Warehouse project documentation -- A case study -- Business intelligence: Beyond the Data Warehouse
"Plan, Design, and Document High-Performance Data Warehouses. Set up a reliable, secure decision-support infrastructure using the cuttingedge techniques contained in this comprehensive volume. Data Warehouse Design: Modern Principles and Methodologies presents a practical design approach based on solid software engineering principles. Find out how to interview end users, construct expressive conceptual schemata and translate them into relational schemata, and design state-of-the-art ETL procedures. You will also learn how to integrate heterogeneous data sources, implement star and snowflake schemata, manage dynamic and irregular hierarchies, and fine-tune performance by materializing and fragmenting views. Work with data- and requirement-driven methodological approaches Create a reconciled database to boost data mart architecture Capture and expressively represent end-user requirements Build a conceptual data mart schema using the Dimensional fact Model Estimate data mart volume and workload Improve performance using advanced logical modeling techniques Extract, transform, cleanse, and load data from operational sources Use sophisticated indexing techniques to optimize query execution plans Comprehensively document data warehouse projects Discover innovative business intelligence techniques." -- P. [4]
Ingeniería de Datos e Intelegiencia
NUEVOSDATOS
