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Streamlining Real-Time Data Integration and Analytics: The Struggle is Over

By   /  July 3, 2018  /  BI / Data Science Articles, BI / Data Science News, Articles, & Education, Big Data Articles, Big Data News, Articles, & Education, Data Articles | Data Science, Business Intelligence, & More, Data Education, Education Resources For Use & Management of Data, Enterprise Information Management, Information Management Articles  /  No Comments

Data Architects and CDOs today face a variety of demands, including delivering Real-Time Analytics, predicting customer behavior, or operationalizing Machine Learning. All of these initiatives share one critical requirement: real-time data. But to get value from real-time data, they must enable continuous collection of data, and on-the-spot integration in-flight across heterogeneous systems. For years, companies […]

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Streaming Analytics 101: The What, Why, and How

By   /  April 26, 2016  /  BI / Data Science Articles, BI / Data Science News, Articles, & Education, Big Data Articles, Big Data News, Articles, & Education, Data Articles | Data Science, Business Intelligence, & More, Data Education, Education Resources For Use & Management of Data  /  No Comments

Stream processing analyzes and performs actions on real-time data though the use of continuous queries. Streaming Analytics connects to external data sources, enabling applications to integrate certain data into the application flow, or to update an external database with processed information. Bloor Research analyst Philip Howard says stream processing is really an evolution of Complex […]

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Mining Big Data for Maximum Value

By   /  June 29, 2011  /  Big Data News, Articles, & Education, Data Daily | Data News, Data Education  /  No Comments

by Angela Guess The Wall Street Journal recently reported on the value of mining Big Data across industry. Citing the McKinsey Global Institute, the article states, “The definition MGI uses for big data is deliberately vague and not based on a specific number. It refers instead to sets of data which are too large for […]

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