Process Mining with Celonis
What you'll learn
- Process mining
- The role of process mining in the broader context of business process management
- Applied process mining with Celonis Free Plan (Formely Celonis Snap)
- Hands-on practical experience with process mining use cases of various degrees of complexity
Requirements
- Students will need a computer with access to the internet not only to follow the course, but also because Celonis Free Plan (Formely Celonis Snap) is a cloud-based application. Some familiarity with working with structured data is required, as process mining often requires a degree of data transformation before ingesting the data into the process mining application.
Description
An important aspect for many organizations is the flow of work between different parts of the organization. Traditionally, experts would use business process modeling techniques to visualize how these processes should be. This is a very labor intensive exercise. Moreover, in practice, the actual process may be very different from what is drawn on paper. This gap can be filled by applying process mining. Process mining uses actual data to visualize what the process is, rather than what the process is thought to be.
Process mining is a relatively young research discipline that sits between computational intelligence and data mining on the one hand, and process modeling on the other hand. The idea of process mining is to discover, monitor and improve real processes by extracting knowledge from data readily available in an organization’s information systems. It is a tool to improve the design, redesign, control, and support of operational business processes.
In this course, students are introduced to the discipline of process mining using a healthy blend of theoretical knowledge and hands-on practice. The theoretical parts of this course are drawn from leading academic publications. The hands-on practice parts will be conducted in the leading process mining software application that is democratizing process mining for the masses, Celonis Free Plan (formely Celonis Snap).
Who this course is for:
This course is most valuable for people that work in an organization in which products and services are the result of processes that leave a digital footprint. Examples are people advising organizations on:
Assembly line industrial manufacturing;
Coordinating patient journeys through a hospital;
The flow of loan applications at a bank;
Logistic coordination and supply chain management;
Customer journeys.
This course will radically transform the ability of students to discover, monitor and enhance these processes
In addition to this, people that work with systems such as Scientific management (Taylorism), Kanban, Kaizen, Lean Six Sigma, Theory of Constraints, Bottleneck Identification and Just-In-Time (JIT) will greatly benefit from this course, because process mining unlocks a data-driven factor into these approaches to production process management.
Other types of students that will benefit from this course are:
Individuals with a background in business process management, process mapping, flowcharting and business process modelling (BPM / BPMN).
Individuals with a background in data science that want to acquire skills that directly contribute to the value chain of organizations.
Individuals responsible for creating a Digital Twin of an organization and/or involved in Robotic Process Automation (RPA) projects (such as UiPath), that need to have a clear grasp on the ongoing processes in an organization in order to be able to prioritize competing process automation projects.
Individuals in charge of process auditing.
Individuals curious about process mining.
What this course is NOT about:
- This course is intended to be hands-on and practical. Therefore, only limited attention will paid to the underlying (alternative) theories of process modelling and mining. The focus will be on applied process mining with Celonis Free Plan (formerly Celonis Snap).
- Although process mining overlaps with the domain of business process modeling & notation (BPMN), this course is not about BPMN. BPMN is only elaborated on in the context that is relevant for process mining, such as conformance checking.
- Although process mining overlaps with the domain of data science, this course is not about data science. Data science is only elaborated on in the context that is relevant for process mining.
- This course will not cover how to integrate Celonis with an organization's information system and/or data warehouse as part of its information architecture.
Who this course is for:
- This course is most valuable for people that work in an organization in which products and services are the result of processes that leave a digital footprint. Examples are supervisors responsible for: Assembly line industrial manufacturing; Coordinating patient journeys through a hospital; The flow of loan applications at a bank; Logistic coordination and supply chain management. This course will radically transform the ability of students to discover, monitor and enhance these processes. People that work with systems such as Scientific management (Taylorism), Kanban, Lean Six Sigma, Theory of Constraints, Bottleneck Identification and Just-In-Time (JIT) will greatly benefit from this course, because process mining unlocks a data-driven factor into these approaches to production process management. Other types of students that will benefit from this course are: Individuals with a background in process mapping, flowcharting and business process modelling (BPM). Individuals with a background in data science that want to acquire skills that directly contribute to the value chain of organizations. Individuals curious about process mining.
Instructor
- 4.3 Instructor Rating
- 1,684 Reviews
- 12,668 Students
- 3 Courses
Dennis Arrindell, MSc., MBA. is a data driven health economist in the field of healthcare financing. He has a significant degree of expertise in statistics, data mining, business intelligence dashboards, machine learning and process mining. As a health economist, Dennis frequently analyzes abstract patterns from highly complex and unstructured health insurance claims data and patient pathways. The discovered insights are used for amongst other things public health research and fraud detection.
In addition to this, he is a research fellow at the Think To Do Institute where he leads statistical research on social and economic matters. Due to this passion for teaching, Dennis is also a part-time teacher of a practical course in Data Warehousing and Data Mining at a local university.
Dennis has a Bachelor's degree in Public Health and a Master's degree in Health economics, both from Maastricht University. He also holds a Master of Business Administration.