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data analytics for IOE 

Big data applications must be able to gather this data and structure it in a way that can create value for organisations. For example, big data applications must account for changing data sources and trends, such as:

• mobility − mobile devices, events, sharing, and sensor integration
• data access and consumption − internet, interconnected systems, social networking, and access models
• ecosystem capabilities − major changes in the information processing model and the availability of an open source framework

As a result, the cost and complexity of these models has increased, prompting changes in the way big data is stored, analysed, and accessed. Organisations must adjust their current data models to accommodate big data. As a result, organisations are increasingly using virtualisation and cloud computing to support their big data needs.

Big data refers to the way in which organisations collect and analyse vast stores of data for insights that can help identify trends, predict behaviour, and empower decision makers. It considers:

• how much data is generated
• how this data is identified and managed as an asset to the organisation
• how this data is turned into usable information
• how organisations use this data to make decisions.

Storage and processing of information is the major application of big data analytics. Internet of Everything (IoE) is the smart connection between people, data, things and processes. This paper studies the available frameworks used for developing secure Internet of Everything with big data analytics. Big data is a collection of data generated from the sensors embedded in the surrounding physical objects

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