Episodes
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In this episode of A Side Of Data, I interview Bernd Ruecker, a co-founder and chief technologist at Camunda - workflow and decision automation platform. We talk about workflow automation, workflow engines, business process modeling notation (BPMN), robotic process automation (RPA).
The episode timeline:
2:00 what are the workflows and what is workflow automation?
4:00 the difference between workflow, process, and routine?
6:00 what are the workflow engines?
8:00 Historical overview of workflow engines and BPMS.
12:00 why using BPMN? What is a good visual representation of the workflow/process
17:00 competition of the BPMN? Powerpoint? Event-driven process chain?
19:00 Process mining tools (DFGs, process maps vs BPMN)
22:00 workflow use case, on the granularity of BPMN model design
26:00 business process use cases vs software engineering use case for the workflow engines
28:40 RPA (robotic process automation) vs workflow automation
35:00 Future of workflow engines
39:00 How to see that your company needs workflow engines?
42:00 As a student, would you study workflow engines?
43:30 How to get started?
Additional info:
Bernd's page: https://berndruecker.io/
Bernd's blog: https://blog.bernd-ruecker.com/
Camunda: https://camunda.com/
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And on the web: asideofdata.com
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Listen to more A Side Of Data:
Building a process mining startup with Raffaele Conforti: https://soundcloud.com/asideofdata/building-a-process-mining-startup-with-raffaele-conforti
New decade for process mining with Wil van der Aalst: https://soundcloud.com/asideofdata/new-decade-for-process-mining-with-wil-van-der-aalst -
In this episode of A Side Of Data, I interview Sebastiaan van Zelst about his experience of building a pm4py python library for process mining.
The show timeline:
1:30 How did pm4py start? The reasons behind
5:30 Why do you need a new library? Why python?
8:00 How big is the library now? What is the current progress
12:00 Categorizing and comparing process mining tools: programming libraries, strand-alone academic, commercial (Apromore, Prom, pm4py, Celonis, Fluxicon Disco, Minit, Process Gold, etc.)
17:30 Problems with commercial tools
20:30 How challenging was to build the pm4py. How easy is it to use the library with the coding workflow on python.
25:40 Projects built on top of the pm4py
29:00 What is available in the library now
32:00 How to start with pm4py and with process mining
34:20 About the PM4Knime project.
37:00 extra: What is the interactive process discovery, how pm4py supports it.
Additional info:
The library: http://pm4py.org
The paper on incremental discovery: https://sebastiaanvanzelst.com/wp-content/uploads/2020/03/Incremental_Discovery_of_Hierarchical_Process_Models__RCIS_1.pdf
Interviewee page: https://sebastiaanvanzelst.com/?page_id=62
Mentioned telegram bot: https://github.com/delas/pmbot
Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
SEND us an email with suggestions: [email protected]
Listen to more A Side Of Data:
Building a process mining startup with Raffaele Conforti: https://soundcloud.com/asideofdata/building-a-process-mining-startup-with-raffaele-conforti
New decade for process mining with Wil van der Aalst: https://soundcloud.com/asideofdata/new-decade-for-process-mining-with-wil-van-der-aalst -
Missing episodes?
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In this episode of A Side Of Data I interview Raffaele Conforti about his experience of building an Australian process mining startup Process Diamond.
Show notes:
2:00 What is process mining for the startup focusing on process mining software
3:30 How do you make a difference between process mining in comparison to data mining and machine learning with clients.
5:00 Is BPM an important for process mining projects?
6:00 Why would you develop a new tool in comparison of using existing tools for consultancy?
9:30 Difference between BPMN and process map
12:00 Problems of a process map and more about BPM models
18:00 About process diamond capabilities
21:00 How can your software compete with more established competitors like Celonis?
22:00 Conformance checking in Process diamond
27:00 Alignment vs business level alignment solutions
29:00 BPMN and conformance checking results. How do they work together?
31:00 What is the story behind the startup?
33:00 Why doing startup in Australia is different to Europe and US
35:00 How is the startup status
36:00 How to get trial of the software
38:00 How much time do you spend on consulting vs coding the startup
Links to Raffaele page:
http://www.raffaeleconforti.com
Link to Process Diamond
http://processdiamond.com
Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
SEND us an email with suggestions: [email protected]
Listen to more episodes of the podcast, like this one:
https://soundcloud.com/asideofdata/new-decade-for-process-mining-with-wil-van-der-aalst -
In this episode of A Side of Data, I interview Jan Mendling about the use of process mining in business process management (BPM) initiatives. We talk about where the real benefit of process mining is when applied to real-world processes and where the limit is.
Jan is a professor at Vienna University of economics and business. He is a successful researcher in the field of information systems, business process management, and process mining, with over 400 research articles published. One of his famous works is 7 process modeling guidelines. He coauthored books, such as Wirtschaftsinformatik and Fundamentals of business process management, the latter is used as a textbook in over 230 educational institutions around the world.
We talk about:
2:00 What is bpm, what processes are and why they need to be managed
7:00 What are information systems
8:00 What is process mining - how the data from information systems is now useful
11:00 Process mining helps accomplish BPM objectives
14:00 How process mining helps process analysts
17:30 Is just seeing how the processes are important? How does it help process analyst. How can you justify price of process mining software?
25:00 Continuous monitoring and auditing with process mining (improvement projects)
27:00 Innovation vs incremental process improvement
34:00 Is there anything that process mining still cannot do in helping BPM?
37:00 Case study with an example of a customer loans
40:30 AB testing of business processes
43:00 What is the future of BPM vs process mining
46:00 is process mining only applicable in BPM scenario?
48:00 Resource recommendations to start with PM and BPM
Jan's page:
http://www.mendling.com/
Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
SEND us an email with suggestions: [email protected] -
In this episode of A Side of Data, I interviewed Wil van der Aalst. He is among the most cited computer science researchers in the world with over 100.000 citations on google scholar and an h-index of 147. He published papers, books, founded conferences, and holds positions at several institutions including RWTH Aachen University, Technical University of Eindhoven, Queensland University of technology, Fondazione Bruno Kessler and others. In addition to academic success, he is also very well known in the industry. The companies that brought his research to the industry are Celonis, Fluxicon Disco, Process Gold, and many others. Because of his influence, he is called a godfather of process mining.
The questions range from the history of process mining, the process mining challenges and solutions, to the future, and various topics connected to the real-world use of process mining.
The episode of long, so here are some time ticks to guide you:
0:00 When was the first time term process mining - (workflow mining) used? How did it appear?
5:00 Why workflow management systems were failures at the end of the 90s
5:30 Process mining vs data mining, machine learning
8:30 What are the main developments in science and industry in the last 20 years]
18:00 Does the industry follow research or it develops also new methods? - doing process mining is not like making a project
21:00 Is process mining aimed at improving how processes work, or to observe how it performs.
23:00 What do you think will happen in the next 10 years to process mining vs what will happen,
34:20 Prescriptive monitoring, recommender systems?
36:00 Machine learning vs formal methods for the future of process mining
38:00 Blockchain, RPA, drift detection, Repairing process models, Data Privacy and process mining
51:00 Are there mistakes you regret in your academic work?
53:00 What recommendations can you give to young researchers
59:00 Questions from entrepreneurs, would you advise creating new tools?
1:05:00 Resources for studying process mining
Resources mentioned in the episode:
Wil's book: https://www.springer.com/gp/book/9783662498507
MOOC: https://www.coursera.org/learn/process-mining
Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
SEND us an email with suggestions: [email protected] -
In this episode of A Side of Data with Corinna Giebler we discuss the topic of data lakes. How is it different from the data warehouse when storing big data in enterprises?
We touch upon questions: How can data lakes influence organizations? Where do they fit in the data science/data management/machine learning pipelines?
We talk about use cases for the technology and which are the main advantages. Also, we give examples of software products.
Links to the resources mentioned in the episode:
[1] Mathis, C. 2017. Data Lakes. Datenbank-Spektrum. 17, 3 (Nov. 2017), 289–293.
[2] Giebler, C. et al. 2019. Leveraging the Data Lake - Current State and Challenges. Proceedings of the 21st International Conference on Big Data Analytics and Knowledge Discovery (DaWaK 2019) (2019).
[3] Fang, H. 2015. Managing data lakes in big data era: What’s a data lake and why has it became popular in data management ecosystem. Proceedings of the 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER 2015) (Jun. 2015).
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And on the web: asideofdata.com
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In this episode of A Side Of Data, I interview Josep Carmona, who is an associate professor at the polytechnic university of Catalonia. He is an active contributor in the range of fields connected to data science, process mining, BPM. Josep is an expert in Conformance checking algorithms who with his team publishes highly cited scientific articles on the topic and recently published a book.
We talk about what process mining and process conformance are, discuss in-depth its types with their advantages and disadvantages. Josep mentions offline and online usages of the conformance checking and metrics of quality. We also discuss several possible use-cases for different aspects of conformance checking
In the end, we also go into the bonus topics such as RPA and process conformance, process drift and conformance checking, process prediction and conformance checking.
Josep's book: https://www.springer.com/gp/book/9783319994130
Process Mining Use Cases:
https://www.win.tue.nl/ieeetfpm/doku.php?id=shared:process_mining_case_studies
His page: https://www.cs.upc.edu/jcarmona/
Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
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In this episode of A Side of Data, we talk with Pol Schumacher who is a Ph.D. in computer science. He is a distinguished Data Scientist at Celonis, a leading process mining company.
In this episode, we talk about what process mining for the industry is, in detail discuss what challenges they face on real-world projects. We discuss all parts of process mining and give additional insights on RPA, privacy (GDPR), what is missing in current tools, etc. Pol gives a prediction of what is going to be relevant for process mining projects in the future.
Pol works with a team that deploys the software, prepares the data models and executes the first process analysis with customers. During those projects he covers a wide range of tasks such as defining the requirements, developing data models and the logic for the generation of the event log, building dashboards within Celonis, setting up end-to-end data pipelines.
Pol Schumacher's page: https://www.linkedin.com/in/pol-schumacher-70047467/
Celonis website: https://www.celonis.com/
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And on the web: asideofdata.com
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This is the second part of the interview.
In this part of the interview with Ingo Weber we talk about his projects involving blockchain technology and discuss recommendations on how to understand if this technology fits any project at hand.
Listen to the first part for the introduction to Ingo's work and introduction to blockchains.
We talk about what is blockchains, what is Ethereum and what it means to execute smart contracts. We touch topics of Business Process Management and how that can be connected and enhanced with blockchains.
Ingo Weber is Professor at TU Berlin, Besides, he is a Conjoint Associate Professor at UNSW Australia and an Adjunct Associate Professor at Swinburne University. He previously was Principal Research Scientist & Team Leader of the Architecture & Analytics Platforms (AAP) team at Data61, CSIRO in Sydney. He has published over 100 refereed papers and three books. His research interests include Business Process Management, Blockchain, Dependability, DevOps, and Artificial Intelligence / AI Planning
Read Ingo's book on blockchain: https://www.springer.com/gp/book/9783030030346
Ingo Weber's page: http://imweber.de/publications.html
Laava: https://www.laava.id
Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
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In the first part of the interview with Ingo Weber we talk about how blockchain technology can enable disruptive change in organizations, including through innovating how the business processes are done.
We talk about what is blockchains, what is Ethereum and what it means to execute smart contracts. We touch topics of Business Process Management and how that can be connected and enhanced with blockchains.
Ingo Weber is Professor at TU Berlin, Besides, he is a Conjoint Associate Professor at UNSW Australia and an Adjunct Associate Professor at Swinburne University. He previously was Principal Research Scientist & Team Leader of the Architecture & Analytics Platforms (AAP) team at Data61, CSIRO in Sydney. He has published over 100 refereed papers and three books. His research interests include Business Process Management, Blockchain, Dependability, DevOps, and Artificial Intelligence / AI Planning
Read Ingo's book on blockchain: https://www.springer.com/gp/book/9783030030346
Ingo Weber's page: http://imweber.de/publications.html
Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
SEND us an email with suggestions: [email protected] -
In this episode we talk with Claudio Di Ciccio about declarative process modelling, and adjacent topics in process mining.
Claudio Di Ciccio is an assistant professor with the Institute for Information Business at Wirtschaftsuniversität Wien, Austria. His research interests include process mining, declarative process modelling, blockchains, and service oriented computing.
In 2015, his paper entitled “Ensuring Model Consistency in Declarative Process Discovery” has received the best paper award of the 13th conference on Business Process Management. In August 2018, he was Researcher of the Month of the Vienna University of Economics and Business.
Recommended PhD theses:
Maja Pešić: “Constraint-based workflow management systems: shifting control to users”
https://doi.org/10.6100/IR638413
Johannes De Smedt: “Studies on Declarative Process Modeling and Its Relation to Procedural Techniques”
https://lirias.kuleuven.be/1834742
Online resources about MINERful
MINERful website: https://github.com/cdc08x/MINERful
MINERful wiki: https://github.com/cdc08x/MINERful/wiki
Slides:
Introductory slides on declarative process specifications: https://www.slideshare.net/cdc08x/introduction-to-the-declarative-specification-of-processes
Slides on declarative process discovery: https://www.slideshare.net/cdc08x/automated-discovery-of-declarative-process-models
Slides on declarative process discovery and reasoning: https://www.slideshare.net/cdc08x/declarative-specification-of-processes-discovery-and-reasoning
Claudio's website:
http://diciccio.net
Papers mentioned during the interview:
The one about activity-events matching (it’s open access!): https://doi.org/10.1007/s10270-017-0603-z
The one about process drift: https://arxiv.org/abs/1907.06386
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And on the web: asideofdata.com
SEND us an email with suggestions: [email protected] -
Today at A Side Of Data, Anton interviews Leo Zhicheng Liu - an information visualization and visual analytics researcher, who is currently working in the Creative Intelligence Lab at Adobe Research.
We talk about visualizing event sequence data. Today there is a lot of interest in this data type for clickstream data, customer journey mapping, medical domain, and process mining. Through his experience of working on many projects including Matrix Wave, SellTrend, CoreFlow, MAQUI(МАРКІ), and Patterns & Sequences, Leo discusses the principles, motivations, and guidelines of creating better visual representations of the data at hand.
Contact Leo via his web page: http://www.zcliu.org/
Leo's twitter: https://twitter.com/zcliu
Leo's projects:
Data Illustrator: https://twitter.com/dataillustrator
CoreFlow: http://www.zcliu.org/coreflow/
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And on the web: asideofdata.com
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In this episode of A Side Of Data, we interview lecturer and assistant professor at the the Queensland University of Technology, creator of Inductive miner Sander Leemans. We discuss how the main algorithm of process mining that is process discovery works, we talk about power and deficiencies of those algorithms, and we also touch upon the process mining tools, and how to improve them. We touch upon process model representations, such as directly follows relations, declare, procedural models. The guest based on his experience advises the creators of the commercial process mining products.
Find more about Sander: http://leemans.ch/leemansCH/quickvisualiser/
On LinkedIn: https://www.linkedin.com/in/sander-leemans-8347b8aa
Find out show on twitter: https://twitter.com/ASideOFData
And on the web: asideofdata.com
Email: [email protected] -
In this episode, my cohost Saimir Bala and me (Anton Yeshchenko) talk about sequential time-oriented event data, which is the basis of the Process Mining as a science about of understanding processes from data. Our discussion covers what are limitations of data mining, and how process mining helps overcome them. We also talk about the main challenges of process mining.
Find us on twitter: twitter.com/ASideOFData
Saimir: twitter.com/saimirbala
Anton: twitter.com/antonyeshchenko
Please rate us on podcasting platforms, and send an email with suggestions for future shows to [email protected] -
In this episode of Aside of data Henderik Proper and Stijn Hoppenbrouwers discuss about conceptual modeling, and how that relates to big data, process mining, BPM. Is conceptual modeling becoming obsolete? Or does it have an impact in the world of machine learning and AI? Why metadata is important? How do organizations benefit from building conceptual models? Reach Henderik at twitter @erikproper and Stijn @SHoppenbrouwers. Tweet to the show @ASideOfData
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In this episode, I interview Moe Wynn, from the Queensland University of Technology in Australia about her experience of helping private companies and hospitals with Process mining. She explains a few practical use cases of how data methods helped actual organizations to find problems in their processes. Additionally, we discuss data quality issues that basically every process mining project encounters and talk about recommendations on what to think about when setting up the ERP system to enable better data analysis afterward.
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This is the introductory episode of A Side Of Data podcast that aims to introduce the listener to the soul of the later episodes. This podcast is all about using data to bring real value and insights through data science, process mining, data visualization algorithms, and going beyond data, to make more sense by the conceptual modeling, BPM, etc. Welcome to the podcast!
Thank you Danial Foroughi for creating an amazing podcast intro
