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What a Big Data Application Security Strategy Includes
Big data application security strategies include integrating tools and processes, preventing APT attacks, user access control, and real-time engine analysis of data.

Big data (bigdata) is a collection of data whose contents cannot be crawled, managed, and processed with conventional software tools in a given time. Big data has five major characteristics, namely, a large number (Volume), high speed (Velocity), variety (Variety), low value density (Value), authenticity (Veracity). It doesn't have statistical sampling methods, it just observes and tracks what happens. The usage of Big Data tends towards the use of predictive analytics, user behavioral analytics, or certain other advanced data analytics methods.

The research organization Gartner defines Bigdata as follows. "Big data" is the need for new processing models to have stronger decision-making, insight discovery, and process optimization capabilities to adapt to the massive volume, high growth rate, and diversity of information assets. [The McKinsey Global Institute defines it as a collection of data that is so large that it greatly exceeds the capabilities of traditional database software tools in terms of acquisition, storage, management, and analysis, and is characterized by four main features: massive data size, rapid data flow, diverse data types, and low value density.