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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.
To be agile, business intelligence and analytics systems need frameworks and metrics to enable stable evolution. Introduction Enterprise Business Intelligence and analytics solutions are complex implementation
Every organization’s analytics strategy should be connected to its data strategy; and every organization should have a data strategy that supports its business strategy Like
Data warehouse / business intelligence / analytics environments require business and IT cooperation for successful architecture and design In working with many large corporations across
Standards are different from guidelines. Standards are firm and must be followed. Successful data warehouses use standards Introduction Many dog owners give their dogs what
Data warehousing is the proven architecture for delivering subject-oriented, stable, analytical information for decision making. Effective data warehouse development provides many business benefits. Introduction A
Organizations can find increased value in business intelligence and analytics efforts through the use of various data delivery strategies. Introduction Like many organizations, your company
Fact Qualifier Matrix capabilities can be expanded to improve the value of conformed dimensions in business intelligence and analytics systems Introduction The venerable Fact Qualifier
There are many benefits to implementing surrogate keys in a dimensional model design for a data warehouse data model Introduction There are many reasons for
Data warehouse implementations are vulnerable to internal as well as external security threats. Follow these mitigating steps to reduce the risks. Introduction Security threats exist
Independent data marts cause many problems in data warehouse architecture; combining to result in numerous issues for business intelligence and analytics solutions. A severe disease
Using a specialized data validity dimension in a data warehouse design can support data quality and analytics capabilities. Introduction While working on an Enterprise Data
Data mining is a powerful analytical activity that can be used with data warehouses and with operational systems, yielding valuable insights. Introduction Data mining is
