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The Data Warehousing concept includes data integration and, conceptual, logical, and physical data models to support business goals and information business needs.
A Data Warehouse (DW) is a data repository that provides a unique and comprehensive view of current and historical data and is critical for a successful Business Intelligence initiative.
Creating a DW requires Mapping data between systems, from source to target as well as capturing details of those transformations into a metadata repository.
Creating a Data Warehousing Architecture, the following patterns must be addressed:
Architectural: Hub and Spoke, BUS, Hybrid
Data Design: Data Structure & Modeling, Data Storage & DBMS
Data Management: Key Management, Time Variance
Data Integration Technology & Techniques: ETL, Data Virtualization, Acquisition, Transformation, Cleansing, Database Loading
Data Usage: Acess, Analysis, Management
(source: Dave Wells)
Keep in mind that, “The success of organizations depends on the intelligent use of available information” (Peter Druker).
Business Intelligence (BI) is a strategic initiative that aim at provide the right information, at the right time, in the right format to generate action, and for What? For decison making purposes.
Decision making (actions) based on useful information is Key to Value generation, for business decision optimization and for companies performance. Based on the best of bread of business intelligence, and Data Visualization standards and User Experience best practices, we build analytic solutions that enables you to control and monitor your business effectively.
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