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Transcript of Big Data
1)Association - looking for patterns where one event is connected to another event
2)Sequence or path analysis - looking for patterns where one event leads to another later event
3)Classification - looking for new patterns
4)Clustering - finding and visually documenting groups of facts not previously known
5)Forecasting - discovering patterns in data that can lead to reasonable predictions about the future
Data mining techniques are used in a many research areas, including mathematics, cybernetics, genetics and marketing. Web mining takes advantage of the huge amount of information gathered by a Web site to look for patterns in user behavior. BIG DATA VOLUME VELOCITY VARIETY Big data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization MAJOR FEATURE Predictive Analytics This is the branch of data mining concerned with the prediction of future probabilities and trends. The central element of predictive analytics is the predictor, a variable that can be measured for an individual or other entity to predict future behavior.
Multiple predictors are combined into a predictive model, which can be used to forecast future probabilities with an acceptable level of reliability. In predictive modeling, data is collected, a statistical model is formulated, predictions are made and the model is validated.
Big data analytics can be done with the software tools commonly used as part of advanced analytics disciplines such as predictive analytics BIG DATA IS THE FUTURE OF THE “INFORMATION AND TECHNOLOGY” INDUSTRY