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Data analytics techniques encompass a variety of methods used to analyze and interpret data for informed decision-making. Descriptive analytics summarizes historical data to identify trends and patterns using statistics, data visualization, and reporting. Diagnostic analytics delves deeper to uncover the reasons behind past outcomes through data mining, correlation analysis, and root cause analysis. Moving forward, predictive analytics utilizes historical data to forecast future events employing regression analysis, time series analysis, and machine learning algorithms. In contrast, prescriptive analytics offers recommendations for action based on data insights, utilizing optimization models, simulations, and decision analysis.
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