One language to rule them all: behavioural querying of process data using SQL
Saved in:
| Title: | One language to rule them all: behavioural querying of process data using SQL |
|---|---|
| Authors: | Brand, Jakob, Kampik, Timotheus, 1989, Okulmus, Cem, Weidlich, Matthias |
| Source: | Process mining workshops Lecture Notes in Business Information Processing. :18-30 |
| Subject Terms: | Process Querying, Process Mining, Pattern Recognition, Computer Science, datalogi |
| Description: | State-of-the-art solutions for process mining rely on proprietary, domain-specific languages to query data recorded during business process execution. To support common analysis tasks, these languages focus on the definition of queries for behavioural patterns. Yet, the use of domain-specific languages for process mining has drawbacks: they require specific user training, lead to a decoupling of the query models for (i) data extraction and transformation, and (ii) the actual analysis, and induce engineering overhead through the development of a dedicated query engine. In this work, we therefore explore the use of standard SQL for process mining tasks. In particular, we demonstrate that the SQL concepts for row pattern recognition as realised by the MATCH_RECOGNIZE clause are sufficient to capture queries for behavioural patterns as specified in the SIGNAL language by SAP Signavio as well as the Process Querying Language (PQL) by Celonis. Based on a discussion of the respective language features, we outline a translation of SIGNAL and PQL queries into standard SQL. This way, we provide the basis for the adoption of widely used, general purpose query engines for process mining tasks. |
| File Description: | electronic |
| Access URL: | https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-237256 https://doi.org/10.1007/978-3-031-82225-4_2 |
| Database: | SwePub |
Nájsť tento článok vo Web of Science | Abstract: | State-of-the-art solutions for process mining rely on proprietary, domain-specific languages to query data recorded during business process execution. To support common analysis tasks, these languages focus on the definition of queries for behavioural patterns. Yet, the use of domain-specific languages for process mining has drawbacks: they require specific user training, lead to a decoupling of the query models for (i) data extraction and transformation, and (ii) the actual analysis, and induce engineering overhead through the development of a dedicated query engine. In this work, we therefore explore the use of standard SQL for process mining tasks. In particular, we demonstrate that the SQL concepts for row pattern recognition as realised by the MATCH_RECOGNIZE clause are sufficient to capture queries for behavioural patterns as specified in the SIGNAL language by SAP Signavio as well as the Process Querying Language (PQL) by Celonis. Based on a discussion of the respective language features, we outline a translation of SIGNAL and PQL queries into standard SQL. This way, we provide the basis for the adoption of widely used, general purpose query engines for process mining tasks. |
|---|---|
| DOI: | 10.1007/978-3-031-82225-4_2 |