Big Data

The massive amounts of data collected over time that are difficult to analyze and handle using common database management tools. The data are analyzed for marketing trends in business as well as in the fields of manufacturing, medicine and science. The types of data include business transactions, email messages, photos, surveillance videos, activity logs and unstructured text from blogs and social media, as well as the huge amounts of data that can be collected from sensors of all varieties (see machine-generated data).

Big Data Storage and Big Data Analytics
The storage industry is continuously challenged as big data increases exponentially. While the physical storage can be enhanced with more terabyte drive arrays, the software infrastructure must be flexible enough to quickly and economically accommodate ever greater volumes of transactions and queries. See Hadoop, Spark and cloud computing.

The analytical challenge is deriving meaningful information from data in petabyte and exabyte volumes. Big data analytics breaks down the data sets into smaller chunks for efficient processing and employs parallel computing to derive intelligence for effective decision-making (see MPP).

Big Data vs. Market Research
Analyzing big data may be able to forecast trends and people's habits without the kind of explanation one would derive from traditional market research. The big data patterns show the next probable behavior of a person or market without a logical explanation as to why. Right, wrong or indifferent, big data has been one of the hottest buzzwords of the 2010s. See Petabyte Age and Google Zeitgeist.

单词	big data
释义	big data big data pl n (Electronics) computing data held in such large amounts that it can be difficult to process Big Data Big Data The massive amounts of data collected over time that are difficult to analyze and handle using common database management tools. The data are analyzed for marketing trends in business as well as in the fields of manufacturing, medicine and science. The types of data include business transactions, email messages, photos, surveillance videos, activity logs and unstructured text from blogs and social media, as well as the huge amounts of data that can be collected from sensors of all varieties (see machine-generated data). Big Data Storage and Big Data Analytics The storage industry is continuously challenged as big data increases exponentially. While the physical storage can be enhanced with more terabyte drive arrays, the software infrastructure must be flexible enough to quickly and economically accommodate ever greater volumes of transactions and queries. See Hadoop, Spark and cloud computing. The analytical challenge is deriving meaningful information from data in petabyte and exabyte volumes. Big data analytics breaks down the data sets into smaller chunks for efficient processing and employs parallel computing to derive intelligence for effective decision-making (see MPP). Big Data vs. Market Research Analyzing big data may be able to forecast trends and people's habits without the kind of explanation one would derive from traditional market research. The big data patterns show the next probable behavior of a person or market without a logical explanation as to why. Right, wrong or indifferent, big data has been one of the hottest buzzwords of the 2010s. See Petabyte Age and Google Zeitgeist. FinancialSeeAIThesaurusSeespark
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