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Predictive analytics brings together advanced analytics capabilities. It extracts information from existing data sets in order to determine patterns and predict future impacts and trends. It forecasts what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessments.[1]
Data analytics encompasses techniques such as regression analysis, pattern matching, forecasting, multivariate statistics, predictive modelling and forecasting. [2]
Augmented analytics is a next-generation data and analytics paradigm that uses machine learning to automate data preparation, insight discovery and insight sharing for a broad range of business users, operational workers and citizen data scientists. Providers now offer augmented analytics capabilities that could disrupt business intelligence (BI) and analytics, data science, data integration and embedded analytic application vendors. [3]
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