A Practical Approach to Automated Business Process Discovery

Yano, Keisuke; Nomura, Yoshihide; Kanai, Tsuyoshi

doi:10.1109/edocw.2013.13

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…Manually approaches to extracting data from relational databases of SAP systems particularly failed to separate events related to various processes; analyzing what was part of the process was hard and time consuming [21,22]. In the generic log extraction approach of [5], the user defines a mapping from from tables and columns to log concepts such as traces, events, and attributes (assuming the existence of a single case identifier to which all events can be related); various works exist to improve finding optimal case identifiers and relations between the identifiers and events [6,7,23]. If the event data is structured along multiple case identifiers as in ERP systems, all these approaches suffers from data convergence and divergence (Sect.…”

Section: Example B -Tables As Artifact Typesmentioning

confidence: 99%

Discovering Interacting Artifacts from ERP Systems

Nagelkerke²,

Wiel³

et al. 2015

IEEE Trans. Serv. Comput.

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The omnipresence of using Enterprise Resource Planning (ERP) systems to support business processes has enabled recording a great amount of (relational) data which contains information about the behaviors of these processes. Various process mining techniques have been proposed to analyze recorded information about process executions. However, classic process mining techniques generally require a linear event log as input and not a multi-dimensional relational database used by ERP systems. Much research has been conducted into converting a relational data source into an event log. Most conversion approaches found in literature usually assume a clear notion of a case and a unique case identifier in an isolated process. This assumption does not hold in ERP systems where processes comprise the life-cycles of various interrelated data objects, instead of a single process. In this paper, a new semi-automatic approach is presented to discover from the plain database of an ERP system the various objects supporting the system. More precisely, we identify an artifact-centric process model describing the system's objects, their life-cycles, and detailed information about how the various objects synchronize along their life-cycles, called interactions. In addition, our artifact-centric approach helps to eliminate ambiguous dependencies in discovered models caused by the data divergence and convergence problems and to identify the exact "abnormal flows". The presented approach is implemented and evaluated on two processes of ERP systems through case studies.

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Section: Example B -Tables As Artifact Typesmentioning

confidence: 99%

Discovering Interacting Artifacts from ERP Systems

Nagelkerke²,

Wiel³

et al. 2015

IEEE Trans. Serv. Comput.

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show abstract

“…Events correspond to updates of the database, i.e., changes of the "state" of the information system. These updates may have been stored in tables of the databases (through in-table versioning like the change tables in SAP or any table that contains dates or timestamps) or can be retrieved using some database log (like redo logs [37,28] explicitly storing all database updates).…”

Section: Introductionmentioning

confidence: 99%

Extracting Multiple Viewpoint Models from Relational Databases

Berti

Aalst

2020

Lecture Notes in Business Information Processing

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Much time in process mining projects is spent on finding and understanding data sources and extracting the event data needed. As a result, only a fraction of time is spent actually applying techniques to discover, control and predict the business process. Moreover, current process mining techniques assume a single case notion. However, in reallife processes often different case notions are intertwined. For example, events of the same order handling process may refer to customers, orders, order lines, deliveries, and payments. Therefore, we propose to use Multiple Viewpoint (MVP) models that relate events through objects and that relate activities through classes. The required event data are much closer to existing relational databases. MVP models provide a holistic view on the process, but also allow for the extraction of classical event logs using different viewpoints. This way existing process mining techniques can be used for each viewpoint without the need for new data extractions and transformations. We provide a toolchain allowing for the discovery of MVP models (annotated with performance and frequency information) from relational databases. Moreover, we demonstrate that classical process mining techniques can be applied to any selected viewpoint.

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“…Other tools/IEs can access the modeling artifacts through the APIs. For example, data from the business process flow are provided to the BPM monitoring tool for monitoring the execution of business processes [15].…”

Section: ) Toole Integration Through Bpm-ie Apismentioning

confidence: 99%

A Metamodel-Driven Business Process Modeling Methodology and Its Integrated Environment for Reusing Business Processes

Yamamoto¹,

Yamamoto²,

Ohashi³

et al. 2018

JSEA

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Reusing business process models and best practices can improve the productivity, quality and agility in the early development phases of enterprise software systems. To help developers reuse the business process models and best practices, we propose a methodology and an integrated environment for business process modeling driven by the metamodel. Furthermore, we propose a process-template design method to unify the granularity and separate the commonality and variability of business processes so that business process models can be reused across different enterprise software systems. The proposed methodology enables to create reuse-oriented business process templates before the business process modeling. To support the proposed methodology, we developed an integrated environment for creating, reusing and verifying the business process models. As the key techniques, we describe the methodology and its integrated environment, including a metamodel and notations. We applied the methodology and integrated environment to an actual enterprise software development project, and evaluated that the productivity of business process modeling is improved by at least 46%. As the conclusion, this paper contributes to prove the effectiveness of the meta-model driven business process modeling methodology for the reuse of business process models.

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A Practical Approach to Automated Business Process Discovery

Cited by 6 publications

References 18 publications

Discovering Interacting Artifacts from ERP Systems

Discovering Interacting Artifacts from ERP Systems

Extracting Multiple Viewpoint Models from Relational Databases

A Metamodel-Driven Business Process Modeling Methodology and Its Integrated Environment for Reusing Business Processes

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