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A data warehouse is an architectural construct of an information system that provides users with current and historical decision support information that is hard to access or present in traditional operational systems. It is also an integrated set of products that enable the extraction and transformation of operational data to be loaded into a database for end-user analysis and reporting. It usually contains historical data derived from transaction data, but it includes data from other sources. It separates analysis workload from transaction workload and enables an organization to consolidate data from several sources. Topics like Data integration , Data warehousing , Mining algorithm .
OMICS International Organizes 1000+ Global Events Every Year across USA, Europe & Asia with support from 1000 more scientific societies and Publishes 700+ Open access journals which contains over 100000 eminent personalities, reputed scientists as editorial board and organizing committee members. The conference series website will provide you list and details about the conference organize worldwide.
Scope and Importance:
Data warehousing, architecture of data warehouse and techniques of data analysis in data warehousing. Query and reporting, multidimensional, analysis, and data mining run the spectrum of being analyst driven to analyst assisted to data driven. Because of this spectrum, each of the data analysis methods affects data modelling.
The Data warehouse market has been achieving strong revenues. The Global Market Statistics shows that it has reached a revenue height of 7.39 USD (billion), 9.15 USD (billion) and 6.12 USD (billion) for services, hardware and software, respectively for the year 2013. The global market statistic also shows a revenue forecast for the global big data market from 2011 to 2017. For 2016, the source projects the global big data market is predicted to grow to more than 45 billion U.S. dollars in revenue.
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This page was last updated on 11th Sep, 2015
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