Abstract
“Big data” implies not only large volumes of data but a wide variety of data types and a high velocity of data streams, with data needed to be integrated from locally within the organization as well as from external sources and distributed locations. New technologies such as Hadoop have been introduced from social media companies to handle vast amounts of unstructured data for analysis. The power of big data comes from using the results of the analysis of the large volumes of unstructured data to make faster and better real-time decisions. Big data architecture includes data integration engines (ETL, ESB, data virtualization), data hubs (master data, data warehouse, document management, Hadoop file system), and metadata support tools (metadata repository, data discovery, data profiling, data modeling). Business intelligence tools and an analytic sandbox are needed to analyze the vast and various structured and unstructured data, and a complex event-processing system is necessary to integrate real-time events with the analysis results to trigger real-time risk and opportunity responses.
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