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Data Science based applications of event sequence analysis: 1. It finds the optimum way of completing the process.Ĩ. This helps remove unnecessary risk and delays. This information table can then be used to draw inferences to improve the business process, by increasing efficiency and effectiveness of process. All these tasks can be transformed into a flow chart of events with information logged into tables as task, time, success/failure and response/ responses (people responsible for the task). Business Application: Most Businesses have a flow of tasks to be done by one or several people at a point of time or after a task and finish it within speculated time. This also helps in managing the big picture and checking if going through analysis/ change as per inferences is worth it.ħ. This mapping must be done in a structured format with a measurement of risks or variation of events involved. The main part of process analysis is mapping the process and recording data without which everything else fails. Old school method involves workflow diagrams or flowcharts but new school method involves database managements systems which are programmed to keep in check flow of tasks, record delays/holdups and keep a stub of responsible people for each task/ delay in the process. Mapping the process: Multiple ways of mapping the process are available. Improving something which we cannot measure: Using process analysis we can develop insights to improve process in future for categorical data based events which is not easily measurable or predictable.Ħ.Post/Pre- effect analysis: Difficult to analyse and maintain time, cost efficiency for post and pre- new effect data analysis without knowing the process side effects.Complete picture may not be visible: If multiple processes are underway, some key insights might be missed which can be analysed better through the new technologies available and proper database maintenance.Opinion interlock: All the people involved in process might have different opinions regarding process and improvements which might not result in anything conclusive or productive.What would happen without event sequence analysis? This helps monitor process health on a proactive basis.Ĥ. Output: Output can be used for process monitoring and mark effects of pre /post new changes effect on events.Algorithm: Event history analysis on data for events such that the algorithm can learn the past behaviour of data in several situations and predict the course of future events as per the scenario.Generally, consists of categorical data in sequences / order. Data: It’s a set of time stamped events data.any new changes can be easily analysed using pre /post effect data change analysis. Benefits? The benefits of event sequence analysis induce cost saving, faster auditing of data and change effect analysis i.e. In simple terms event sequence analysis is the analysis of data which has been transformed into logs of various events which in subsequent order form or lead to the completion of one big process.Ģ.