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A data warehouse is an environment that combines an integrated decision support database with software to perform extraction transformation loading processes from a variety of operational and external sources. These technologies are combined to support historical, analytical, and business intelligence (BI) requirements.
A business intelligence (BI) process collects, stores, and analyzes the data produced by a company’s activities. BI encompasses data mining, process analysis, performance benchmarking, and descriptive analytics. BI produces reports, analysis, and other supports analytical best practices.
There are challenges that can be encountered in any organization when analyzing data for decision-making. Applying the optimal solution to each analytical challenge can improve
Best practices for staffing any data warehouse / business intelligence /analytics initiative should be followed to ensure success and sustainability. Every major program or initiative
Team management is a crucial factor in the development and implementation of all successful data warehouse and analytics programs. Just as it is important to
Defining the optimal organizational structure for a data warehouse, business intelligence, analytics program is a critical success factor that starts with the proper foundation. There
Data provides more reliable insight into organizational outcomes than intuition alone can. That’s why most managers build dashboards to monitor their sales pipeline, revenue generated,
Not all business intelligence / analytics efforts must be large, multi-phased initiatives. Small, focused, quickly completed projects can provide lasting value to any organization. Small,
Industries with broad and deep data collections, such as healthcare, require extensive business intelligence and analytical solutions to address their decision-making needs. Most healthcare providers
Successful project managers present realistic expectations for completing any effort. Managing expectations for delivery is crucial to the perception of success, especially with business intelligence
Is your business intelligence environment ready for safe, reliable, scalable accessibility via the Internet? How are you addressing this challenge? Typically, business intelligence (BI) environments
It is important to understand the value of capturing as much detailed root data as possible to enable the development and usage of views and
It is important to determine expected usage patterns for business intelligence and analytical applications before design, and to evaluate their actual usage after implementation to
Every data warehouse and business intelligence initiative has risks. Learn to identify them at the start and select the optimal remedy or mitigation technique to
