OUTLIERS DETECTION & WHAT IF ANALYSIS
Simulate different scenarios to offer different possible outcomes. Find values that deviate from other observations on data.
Identify abnormal behavior to detect issues, information breaches, problems, structural defects, and other malfunctions. Outliers can potentially skew or bias any analysis performed on the dataset. It is therefore very important to detect and adequately deal with outliers.
What-if analysis allows the evaluation of advantages and disadvantages by comparing different solutions which in turn, allows you to safeguard your action. Comprehensive alternatives to solutions and there related impact can be evaluated and validated with what-if analysis. The consequences of any events (late delivery etc.) can be predicted. Especially effective is the what-if analysis in combination with other flexis technologies such as Live Analytics and Optimization.