Characteristics of big data analysis (including visualisations)



Big data analysis is a process of looking at datasets for useful information, every dataset has their own characteristics


Volume- This refers to the datasets that are voluminous (large in size) when there is large volumes of data to analyse traditional big data analysis becomes ineffective as it works better with small amounts of data


Varity- This refers to different types of data that is found when doing data analysis. this could either include non-structured and semi structured data.


Velocity- Velocity refers to the speed of the data analysis. since data can become old or less valuable over time it is important that it is analysed quickly.


Visualization- Visualisation is a form of analysis using visual methods to represent datasets for people. Data presented in this way is simple and easy to understand.


Machine learning- Machine learning is about the use of machine learning algorithms to spot patterns in the big data. after a while you will be able to use the data gathered for predictions and forecasts


Scalability- this refers to the tools used to analysis the data itself. the tools include specific types of hardware and software used in the process.


Collaboration- This refers to tools that make the process of big data analysis smoother and easier to understand. collaboration is done by using different types of virtualization software to visualise the findings

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