Modern enterprise business intelligence and data management a roadmap for IT directors, managers, and architects
Nearly every large corporation and governmental agency is taking a fresh look at their current enterprise-scale business intelligence (BI) and data warehousing implementations at the dawn of the ""Big Data Era""...and most see a critical need to revitalize their current capabilit...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Waltham, Massachusetts :
MK
2014.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628222406719 |
Tabla de Contenidos:
- Cover; Title Page; Copyright Page; Table of contents; Preface; Terminology; Defining "Enterprise"; Defining "Data"; Defining "Enterprise Data Management"; Defining "Business Intelligence"; About the author; Chapter 1 - The Rebirth of Enterprise Data Management; 1.1 - In the beginning: how we got to where we are today; 1.1.1 - 1960's and 1970's; 1.1.2 - 1980's; 1.1.2.1 - Enterprise Data Models; 1.1.2.2 - Distributed Database Management Systems (DDBMSs); 1.1.3 - 1990's; 1.1.3.1 - Data Warehousing; 1.1.3.2 - Read-Only Distributed Data Access; 1.1.4 - 2000's; 1.1.5 - Today
- 1.2 - A manifesto for modern enterprise data management: what are we trying to accomplish? 1.2.1 - Bringing Order to an Organization's Data, Reporting, and Analytics; 1.2.2 - Supporting Emerging Technologies and New or Enhanced Applications; 1.2.3 - Turning "Data is our Lifeblood" and "The Data-Driven Organization" into More than Just Slogans; 1.2.4 - Aligning Our Approach and Architecture with Our Organizational Structure and Culture; 1.3 - Chapter summary; Chapter 2 - Assessing Your Organization's Current State of Enterprise Data Management; 2.1 - Introduction
- 2.2 - A rapid, consensus-driven starting point to current state assessment 2.2.1 - Step 1: Determining the Scope and Scale of the Enterprise; 2.2.2 - Step 2: Complete a 4-by-4 Assessment Scorecard; 2.2.2.1 - Complexity Index; 2.2.2.2 - Quality Index; 2.2.2.3 - Support Index; 2.2.2.4 - Tension Index; 2.3 - Category 1: operational reporting and querying; 2.4 - Category 2: strategic insights; 2.5 - Category 3: data architecture; 2.6 - Category 4: work processes and human/organizational factors; 2.7 - Building and grading the 4-by-4 scorecard; 2.8 - Interpreting the meaning of the results
- 2.9 - Chapter summary References; Chapter 3 - Identifying and Cataloguing Key Business Imperatives; 3.1 - Introduction; 3.2 - Cross-brand, cross-geography strategic sourcing; 3.3 - Lean manufacturing; 3.4 - "Mega-processes"; 3.5 - Heightened risk mitigation and management; 3.6 - Enterprise systems initiatives; 3.6.1 - New ERP Implementation; 3.6.2 - Enterprise Systems Migration; 3.6.3 - Enterprise Systems Rationalization and Consolidation; 3.7 - Enterprise-level business quality initiatives; 3.8 - Chapter summary; References
- Chapter 4 - Surveying Relevant Enterprise Data Management Technologies 4.1 - Introduction; 4.2 - Databases and data storage; 4.3 - Database administration and maintenance; 4.4 - Data virtualization; 4.5 - Master data management; 4.6 - Metadata management; 4.7 - Data quality and profiling; 4.8 - Data governance; 4.9 - Data interchange and movement; 4.10 - Data retrieval, preparation, and delivery (business intelligence, reporting, and analytics); 4.11 - Other core and enabling technologies; 4.12 - Staying on top of proliferating technologies; References
- Chapter 5 - Building an Enterprise Data Management and Business Intelligence Roadmap
