Data And Data Of Data

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Data: Data is studied as the lowest part of abstraction level from which knowledge and information can be derived. Data is always a raw form of information. It can be a collection of images, numbers, inputs, characters or any other outputs that can be converted into symbolic representation.
Information: Information refers to data that provides a meaningful connection between them. Here, data refers to the collection that can be processed to provide useful answers which leads to an increase in knowledge.
Knowledge: Knowledge terms to the collection of a set of information, so that it provide something useful. We express our knowledge by the way we act on information provided to us.
2- DATA STREAM
In recent years, the processing and
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These characteristics of data stream pose a huge challenging problem in this field. Many algorithms for data stream mining have been developed in scientific and business applications.

3- DATA STREAM MININIG
Fig 2 from http://dspace.cusat.ac.in/jspui/bitstream/123456789/3616/1/report_doc.pdf

Data stream mining refers to the extraction of informational structure from continuous and rapid data streams. It poses a lot of challenges varying to different aspects that include problems related to storage, computational, querying and mining. For the past recent years, data mining research have gained due to an extra ordinary increase in computing power and increasing data of streaming information. Due to an increase number in the database sizes and computational power, many algorithms and techniques have been developed within the past few years. Because of these data stream requirements, it is important to design new techniques other than the traditional methods that would require the data to be first stored in their database and then pre-processing it using scientific and complex algorithms that makes several pass over data and the data is generated with high rate which is very difficult to store. This causes two research challenge:
• Fast Mining methods requires to be developed: for example, algorithms that only require one pass on data and have limited memory
• Need to
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