Historically, business intelligence and data warehouses have been
associated with back office employees. In the 1990s, data was
integrated and loaded nightly, optimized for trend reporting and
strategic analysis, and delivered via reporting tools. Back office
planners running pre-defined reports were the bedrock users of
business intelligence (BI). Over time, knowledge workers evolved
to demand richer, more diverse insights. As usage matured,
requirements to include predictive analytics, event-driven alerts,
and operational decision support have become the norm.While
demand for near real-time information always existed in front
office operational communities, the costs and complexity of
loading data multiple times per day kept data out of reach. This
caused expert database administrators and innovative software
vendors to find ways of reducing data latency between source
systems and the data warehouse (DW) to serve up “just-in-time”
insights throughout the business day.
Table of Contents
- Pervasive Business Intelligence
- Pervasive BI Applications
- Pivotal Role of the CIO
- Pervasive BI Reference Architecture
- Decision Repositories: Active Data Warehousing
- Tactical Decisions
- Prioritizing Mixed Workloads
- Mission Critical Data Warehouses
- Data Integration Services
- What is a Data SLA?
- How do we achieve the Data SLA?
- Decision Services - Pervasive BI for Front-Line Users
- BI Service Level Agreements
- Pervasive Analytics
- Delivery Mechanisms for Pervasive BI
- Decision Services for Pervasive BI
- Success Factors Summary