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In the Process optimization team, you will have the opportunity to work on exciting technologies on big event logs of processes where the process performance and resource behavior matter.
Query languages are widely used for exploring data and answering various analysis questions from data. SQL is the first choice for work with relational data. However, process data are typically recorded in the form of event with timestamps, and often analyzed in the context of the sequence of events generated by the same process instance, or by multiple related process instances. The analysis of this kind of data with SQL by the process analyst is difficult, and often even impossible as it requires writing complex queries. As a result, most tools addressing process optimization problems implement their own, relatively simple in use, query languages meeting the needs of process analysts. Historically, most of them imply a so-called flat event log model, i.e., they consider execution of each process instance in isolation.
ServiceNow platform for managing digital workflows has a process optimization component, that implements a query language for the flat event log model as well. However, considering process instances in isolation significantly limits the process analysis capabilities. There are business cases requiring the analysis of multiple cases of the same process, single cases of multiple processes, and multiple cases of multiple processes together for taking their interactions into account.
Although this problem is addressed in recent work, the requirement for the language simplicity is not fully solved, and the proposed implementation is technically infeasible for using in ServiceNow’s cloud environment.
The goal of this project is to design an extension of the existing query language implemented in the process optimization component such that:
- it implements the given user stories related to the analysis of multiple process instances of multiple processes together,
- it is simple enough to be used by business users after a brief crash course, without extensive trainings,
- it meets the internal software, hardware, security, and performance requirements.
The designed extension, or at least its part should be implemented as a prototype and evaluated on datasets provided by ServiceNow.
What you should know before you get here:
- working towards a MS in a related field,
- coursework in process mining,
- coursework in relational or graph database concepts,
- strong analytical and problem-solving skills,
- be a self-starter and possess a strong sense of self-motivation,
- hands-on exposure via academic or professional/internship experience with a programming language, preferably Java.
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