Big data describes datasets with volumes so huge they are beyond the ability of

Big data describes datasets with volumes so huge they

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Big data describes datasets with volumes so huge they are beyond the ability of typical database management system to capture, store, and analyze. The term doesn’t refer to any specific quantity of data but it’s usually measured in the petabyte and exabyte range. It includes structured and unstructured data captured from Web traffic, email messages, and social media content like tweets and status messages. It also includes machine-generated data from sensors. Big data contains more patterns and interesting anomalies than smaller data sets. That creates the potential to determine new insights into customer behavior, weather patterns, financial market activity and other phenomena. Hadoop: Open-source software framework that enables distributed parallel processing of huge amounts of data across inexpensive computers. The software breaks huge problems into smaller ones, processes each one on a distributed network of smaller computers, and then combines the results into a smaller data set that is easier to analyze. It uses non- relational database processing and structured, semi-structured and unstructured data. In-memory computing: rather than using disk-based database software platforms, this technology relies primarily on a computer’s main memory for data storage. It eliminates bottlenecks that result from retrieving and reading data in a traditional database and shortens query response times. Advances in contemporary computer hardware technology makes in-memory processing possible. Analytic platforms: Uses both relational and non-relations technology that’s optimized for analyzing large datasets. They feature preconfigured hardware-software system designed for query processing and analytics. List and describe the components of a contemporary business intelligence infrastructure. Business intelligence (BI) infrastructures include an array of tools for obtaining useful information from all the different types of data used by businesses today, including semi- structure and unstructured big data in vast quantities. Data warehouses, data marts,
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Hadoop, in-memory processing, and analytical platforms are all included in BI infrastructures. Powerful tools are available to analyze and access information that has been captured and organized in data warehouses and data marts. These tools enable users to analyze the data to see new patterns, relationships, and insights that are useful for guiding decision making. These tools for consolidating, analyzing, and providing access to vast amounts of data to help users make better business decisions are often referred to as business intelligence. Principal tools for business intelligence include software for database query and reporting tools for multidimensional data analysis and data mining.
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