Ainda precisamos de um Data Warehouse

Recommendations

Info

Key Issues 1. What aspects of a data warehouse methodology are still required? 2. How does the concept of a logical data warehouse balance the needs of agility and governance? 3. What are your architectural options? 13 © 2015 Gartner, Inc. and/or its affiliates. All rights reserved.
Use-Case Access Semantics Semantics Form a Bridge to <strong>Data</strong> Science & New Practices Veracity COMPROMISE SLA Requirements Repositories 80% of Analytics Infrastructure Is the Same as It Ever Was. Taxonomy/Ontology Resolution And/Or /=/~ Fe<strong>de</strong>ration/ Virtualization Variability Auditing and Management Statistics And/Or CONTENDER 10% Need Flexibility and Short Duration. Distributed Process DQ, MDM, Gov. ? Metadata High Value CANDIDATE 5% Converting Structure on Read and Integrated. SCIENCE SANDBOX 5% Constant Experimentation and Exploration: • 80/10/5 Rule Again! A Semantic Tier Is How You Move From a Binary Design That Forces Unnatural Dichotomy and Creates a More Flexible and Responsive Architecture. 14 © 2015 Gartner, Inc. and/or its affiliates. All rights reserved.
Page 1 and 2: Gartner Business Intelligence & Inf
Page 3 and 4: Key Issues 1. What aspects of a dat
Page 5 and 6: What Is a Data Warehouse? • Archi
Page 7 and 8: You Still Need All of the Analytics
Page 9 and 10: Funding the Need Somewhere Else Doe
Page 11 and 12: % of volume contribution "New" Big
Page 13: Use-Case Access Semantics Tradition
Page 17 and 18: Integration Semantic Interface Arch
Page 19 and 20: Option No. 1: BI Platform as Semant
Page 21 and 22: Option No. 3: Virtualization as Sem
Page 23: Recommended Gartner Research Foc

Ainda precisamos de um Data Warehouse

Create successful ePaper yourself

Delete template?

Save as template?