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KNIME Spring

Summit 2024

April 15-17 | Austin, TX | AT&T Hotel & Conference Center

3 Days of Data Science in Action

Join your peers for KNIME Spring Summit 2024 in Austin, TX or online. Hear from business and data experts how they are building and scaling the adoption of data analytics, genAI, and machine learning in multiple industries. Take an instructor-led onsite training and get first-hand news of the latest updates in KNIME software.

Meet the speakers

matt_wulff-2

Matt Wulff

CareerBuilder
Head of Analytics
Hokuto Fujii, Yamaha Motor

Hokuto Fujii

Yamaha Motor
Data Science Strategy Lead
Marcel Meyer

Marcel Meyer

Siemens Healthineers
Head of Data Governance and Management
Michael Berthold

Michael Berthold

KNIME
CEO & Co-Founder
Michael_Richter-2

Michael Richter

Hennessy Automobile Companies
Director of Business Intelligence
Katie - ring-2

Kate Bartkiewicz

digData
Marketing Data Scientist & Owner
Prof. Shanaka-ring (1)

Dayanjan Shanaka Wijesinghe

VCU, School of Pharmacy
Associate Professor
Fabiola_Martina-ring (1)

Fabiola Martina

Siemens Healthineers
Operational Excellence Manager
Behrooz.Davazdahemami-ring (1)

Prof. Behrooz Davazdahemami

University of Wisconsin - Whitewater
Assistant Professor
Lee Fader

Lee Fader

Congruence Therapeutics
Vice President, Chemistry
Jerome Treboux

Jerome Treboux

Forest Grove
Senior Consultant
Dakshitha Narendra Kiranakankanamage

Dakshitha Narendra Kiranakankanamage

ElectraNet
Asset Information Analytics Engineer
Selman Bayoglu

Selman Bayoglu

Kuveyt Türk Participation Bank
Head of Treasury Marketing
Ricardo - ring

Ricardo Auerbach

BENTELER
Process Engineer - Hot Rolling Mill
Iris - ring

Iris Adä

KNIME

VP Data & Analytics

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matt_wulff-2

Matt Wulff

CareerBuilder
Matt Wulff is the Head of Analytics at CareerBuilder and a trusted source for job opportunities and advice. In his current role, Matt oversees a team of analysts that provide data, analysis, and reporting to the sales, finance, product organizations.
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Hokuto Fujii, Yamaha Motor

Hokuto Fujii

Yamaha Motor
Hokuto Fujii is Yamaha Motor's AI hero and works as a data scientist himself and as a project leader. Hee built a training program with the aim of helping employees use data as a matter of course, and is promoting the use of AI in actual work that Yamaha is promoting.
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Marcel Meyer

Marcel Meyer

Siemens Healthineers
Marcel Meyer is leading the Data Governance and Management function for CRM Excellence at Siemens Healthineers. With over 20 years of professional experience in various functions such as Supply Chain, Finance, CRM, and Project Management on various levels across a multinational company, he and his team innovate the way data is made available, usable, and accessible in a business-friendly way for sales teams and sales leaders within Siemens Healthineers. Marcel is living and working in the greater area of New York, USA.
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Michael Berthold

Michael Berthold

KNIME
Michael Berthold is co-founder and CEO of KNIME, the open analytics platform used by thousands of data experts around the world. Michael has co-authored two successful data analysis text books and is a frequent speaker at both academic and industrial conferences. If time permits he still builds workflows.
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Michael_Richter-2

Michael Richter

Hennessy Automobile Companies

Michael Richter, a seasoned professional in Business Intelligence, passionately leverages data-
driven insights to excel in driving business excellence. With 20+ years of experience in the automotive and financial sectors, Michael consistently transforms raw data into actionable strategies, completing the last mile. As an industry leader, he has led successful initiatives, including implementing advanced BI solutions with KNIME and its community.

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Katie - ring-2

Kate Bartkiewicz

digData
Kate is a seasoned data-scientist who has been working with Fortune 500s and high-growth startups for over 15 years. She has extensive experience building automated analytics solutions specifically designed to surface marketing inefficiencies, identify key customer segments, and lead experimentation. Her marketing attribution models have been used to optimize billions of marketing dollars globally.

Kate is a KNIME fanatic and uses it for everything – including to power the analytics SaaS she founded and led to MVP, where it had more than 250 users and raised more than $1M in investment.
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Prof. Shanaka-ring (1)

Dayanjan Shanaka Wijesinghe

VCU, School of Pharmacy
Shanaka, a tenured Associate Professor at Virginia Commonwealth University School of Pharmacy, excels in metabolomics, lipidomics, and digital health. His Ph.D. in Biochemistry and Molecular Biology from VCU underpins his expertise. Dr. Wijesinghe pioneers AI and XR integration in healthcare and education. He's lauded for innovative teaching, notably with "Pharmacists for Digital Health," fostering self-learning and digital healthcare solutions. Instrumental in founding the Digital Health Innovation Lab, he empowers students to create digital health applications. His AI and XR initiatives reshape healthcare and education, bridging technology and practice, and influencing healthcare delivery and education significantly.
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Fabiola_Martina-ring (1)

Fabiola Martina

Siemens Healthineers
As an experienced leader at Siemens Healthineers, Fabiola excels in navigating the complex world of financial process automation. She plays a pivotal role in the Customer Finance department, enhancing operational efficiency through strategic process automation. Her unique understanding of automation tools and financial processes drives productivity within the organization, a success she attributes to her dedicated team. Off-duty, Fabiola enjoys Maryland's vibrant lifestyle, cooking, baking, and spending quality time with her son, Carlo.
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Behrooz.Davazdahemami-ring (1)

Prof. Behrooz Davazdahemami

University of Wisconsin - Whitewater
ِDr. Behrooz Davazdahemami is an Assistant Professor of Information Technology and Supply Chain Management (IT&SCM) at the University of Wisconsin-Whitewater. He received his M.S. in Industrial Engineering from University of Tehran and his Ph.D. in Management Science and Information Systems from Oklahoma State University. His research interests include health analytics, business analytics, explainable AI, IT privacy, and technology addiction. He is a member of the Association for Information Systems, The Institute for Operations Research and the Management Sciences (INFORMS), and the Decision Sciences Institute. He has published in reputable journals such as Decision Support Systems, Journal of Business Research, Information & Management, and Annals of Operations Research, as well as IS conference proceedings such as the Hawaii International Conference on System Sciences (HICSS) and the International Conference on Information Systems (ICIS).
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Lee Fader

Lee Fader

Congruence Therapeutics
Lee Fader has 18 years of experience in the pharmaceutical industry and now holds the role of Vice president of Chemistry at Congruence Therapeutics. Here, he leads small molecule drug discovery efforts from the Intersection of medicinal chemistry, computational chemistry, and artificial intelligence to discover new medicines for patients suffering from rare diseases.
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Jerome Treboux

Jerome Treboux

Forest Grove
Jerome is an experienced data scientist with over 10 years of expertise working on data science projects in various industries, including energy, medicine, tourism & agriculture. Holding a Master's degree in Business Administration and a Ph.D. in Computer Science specializing in machine learning and image analysis, he offers a unique combination of technical prowess and business insight. Jerome shared his expertise as a lecturer at the University of Applied Sciences and Arts, Western Switzerland, and is currently employed at Forest Grove in Australia. Proficient in the KNIME platform since 2011, Jerome has spearheaded numerous projects, ranging from ETL to advanced analytics. He is a highly sought-after in the data science world, driving transformative solutions across industries.
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Dakshitha Narendra Kiranakankanamage

Dakshitha Narendra Kiranakankanamage

ElectraNet
Dakshitha Narendra Kiranakankanamage is an Asset Analytics Engineer at ElectraNet, the electricity transmission network service provider of the state of South Australia. Dakshitha holds a Bachelor of Computer Systems Engineering (Hons) from the University of Adelaide.  As member of ElectraNet’s Asset Information team, he works on reporting, workflow automation and data governance whilst engaging with various Principals from multiple disciplines. His interests include business analytics, process improvement, change management and empowering people and community through technology - an ally of continuous improvement and lifelong learning.
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Selman Bayoglu

Selman Bayoglu

Kuveyt Türk Participation Bank
He has been driving results at Kuveyt Turk Participation Bank’s Treasury Group since 2011, bringing a deep passion for generating value for all stakeholders. His expertise spans a broad spectrum, from mastering Treasury Marketing Management and navigating the complexities of Big Data & Business Analytics to unlocking potential with Data Science. He is renowned for elevating strategies through Advanced Marketing Analytics, leading the digital and real-time marketing initiatives, and specializing in Capital Markets, FX, and Precious Metals.Outside his professional realm, he serves on the Harvard Business Review Advisory Council,where he enjoys sharing forward-thinking insights on leadership and management's evolving landscape. Beyond his contributions to the leadership and management fields, his personal life is equally vibrant. He expresses his creativity and maintains his productivity through various artistic and physical activities. Whether it's playing the reed flute and piano, craXing poetry, riding a waveboard, skateboarding, swimming, roller-skating, or ice-skating, he embodies a multifaceted approach to life that blends professional excellence with personal passions and hobbies.
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Ricardo - ring

Ricardo Auerbach

BENTELER

Ricardo is a Process Engineer in the Hot Rolling Mill at Benteler Steel/Tube. He graduated from Louisiana Tech University with his Industrial Engineering degree and Six Sigma Black Belt Certification. Leveraging KNIME and his statistical analysis capabilities, Ricardo works at the data-driven, state-of-the-art seamless pipe mill every day to drive performance, reliability, and quality.

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Iris - ring

Iris Adä

KNIME

For more than 10 years Iris has been spending her days with KNIME and her evenings in Heidelberg. On her journey to KNIME she studied mathematics and computer science at the University of Konstanz and developed her passion for data science. Iris is responsible for the Technical Customer Care Team and enjoys working on projects such as KNIME Model Factory or the Workflow Coach.

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Why attend

Level up your skills: Whether you’re new to data science or a data expert, we’ve got a course for you.

Explore latest tech updates: Get sneak peeks into advances in KNIME software.

Network: Connect with industry leaders and new peers in social breakouts, at the partner expo, and the summit party.

Plan Your Arrival

Location & Accomodation

Welcome to the location of the KNIME Spring Summit 2024:

AT&T Hotel and Conference Center

1900 University Avenue Austin, TX 78705  Map

 

Book your room here and enjoy staying onsite to network more and travel less.

KNIME discounted rates across 4 nights, Sun 14 - Wed 17 April.

Pricing and room availability is not guaranteed after March 29, 2024.              Limited rooms available! 

You must use this link for our KNIME rate. (Bfast included in Summit Pass)

Book the hotel →

Onsite Only

Training Sessions

 

L1-DW | Analytics Platform for Data Wranglers: Basics

TRAINING 1: 10:00AM - 5:30PM

This course is designed for those who are just getting started on their data wrangler journey with KNIME Analytics Platform. It starts with a detailed introduction of KNIME Analytics Platform - from downloading it through to navigating the workbench. 

The course focuses on accessing, merging, transforming, fixing, standardizing, and inspecting data from different sources. It dives into data cleaning and aggregation, using methods such as advanced filtering, concatenating, joining, pivoting, and grouping. And lastly learn how to visualize your data. With all of this, you’ll learn how to get your data into the right shape to generate insights quickly.

We’ll take you through everything you need to get started with KNIME Analytics Platform, so you can start creating well-documented, standardized, reusable workflows for your (often) repeated tasks. This course lets you put everything you’ve learnt into practice in a hands-on session based on real-world use cases.

What level of KNIME experience is needed for this course?
None! We’ll start right from the beginning and teach you everything you need to know to get your data wrangling done with KNIME Analytics Platform.

L2-DW | Analytics Platform for Data Wranglers: Advanced

TRAINING 2: 10:00AM - 5:30PM

This course builds on the KNIME Analytics Platform Course for Data Wranglers: Basics by introducing advanced concepts for building and automating workflows. 

Learn all about flow variables, different workflow controls such as loops, switches, and how to catch errors. And lastly learn how to export your results, format your Excel tables, and look beyond data wrangling towards data science, training your first classification model. 

During the course there’ll be hands-on sessions based on real-world use cases.

What level of KNIME experience is needed for this course?
You should already know how to build workflows using KNIME Analytics Platform. This course doesn’t provide an introduction to KNIME Analytics Platform - it focuses on more advanced concepts of automating and building workflows.

L3-DA | Productionizing Data Apps

TRAINING 3 10:00AM - 5:30PM

You have developed a nice data app with KNIME Analytics Platform. What are the next steps to productionize it? In this course we will show you what to do to get your data app up and running, including: testing, deployment on KNIME Business Hub, permissions & versioning, custom styling, orchestration, and more.

The course includes sentiment analysis workflows that can be used over any type of text, and a “what country has this flag?” game that is implemented as a data app. Besides learning about data apps in KNIME, you will have multiple workflows that can be adapted to your needs by the end of the course. 

In the first session of this course, you will learn what needs to be checked before deploying a data app on KNIME Business Hub. In the second session, you will be introduced to KNIME Business Hub — including how to upload workflows and deploy them as data apps or workflow schedules. Next, in the third session, you will learn how to create interactive data apps that can be deployed on KNIME Business Hub and made available as web browser applications. Finally, in the fourth session, you will learn about runtime optimization, workflow orchestration, and general best practices. We wrap up in a fifth session with exercise solutions. 

At the end of each session, we will provide some practical exercises to test and apply your knowledge.

L4-DE | Best Practices for Data Engineering

TRAINING 4: 10:00AM - 5:30PM

This course focuses on how to use KNIME Analytics Platform for data engineering and how to apply best practices when building data processing pipelines.

Learn the concepts behind connecting to multiple data sources, the methods for data anonymization, and advanced database topics. Be introduced to the Apache Hadoop ecosystem and find out how to handle big data with the Apache Spark integration. Finally, learn how to build and orchestrate modular workflows.

Put your knowledge into practice with hands-on exercises to build and orchestrate two applications: first, extract, validate, transform, blend, anonymize, and load the customer data to a database; second, use Spark to access, impute missing values, and aggregate the website usage data. 

This is an in-person instructor-led course run by our KNIME data scientists. 

What level of KNIME experience is needed for this course?
This course doesn’t provide a detailed introduction to KNIME Analytics Platform. You should be competent in using KNIME Analytics Platform. We expect that you have already built KNIME workflows and are aware of the workflow control concepts such as flow variables, loops, switches, and error handling. We recommend taking this course after obtaining the L1 and L2 KNIME proficiency or equivalent.

L4-DV | Low Code Data Extraction and Visualization

TRAINING 5: 10:00AM - 5:30PM

Some of the common topics on data extraction today include how to extract from exotic sources like websites and how to use REST services. Once the data is extracted, what is the best way to visualize that data in order to pitch or sell an idea? To answer this question, it is best to arm yourself with a small collection of low code data extraction and visualization tools.

In this course, we offer the chance to learn more about advanced data extraction techniques and advanced visualization including dashboards. We introduce a useful low code tool for data extraction as well as various visualizations. We begin the course with the basics of creating simple dashboards, and conclude with interactive and refined user interfaces. In addition, we also demonstrate how to extract text data from various sources using Regex. 

This is an in-person instructor-led course run by our KNIME data scientists. 

What level of KNIME experience is needed for this course?
This course doesn’t provide a detailed introduction to KNIME Analytics Platform. You should be competent in using KNIME Analytics Platform. We expect that you have already built KNIME workflows and are familiar with concepts and techniques for data wrangling. We recommend taking this course after obtaining the L1 and L2 KNIME proficiency or equivalent.

 

L4-ML | Introduction to Machine Learning Algorithms

TRAINING 6: 10:00AM - 5:30PM

This course introduces you to the most commonly used machine learning algorithms used in data science applications. 

We will explore different supervised learning algorithms for classification and numerical problems such as decision trees, logistic regression, and ensemble models. In addition, we will introduce techniques such as neural networks and deep learning. We will also examine unsupervised learning techniques, such as recommendation engines, as well as various clustering methods including k-means, hierarchical clustering, and DBSCAN. 

We will also discuss various evaluation metrics for trained models, and showcase a number of classic data preparation techniques, such as normalization and dimensionality reduction.

This is an in-person instructor-led course designed for current and aspiring data scientists eager to learn more about machine learning algorithms used commonly in data science projects.

What level of KNIME experience is needed for this course?
You must be competent in using KNIME Analytics Platform. We strongly recommend you be at the level of an advanced KNIME user -  for example you’ve taken a basic and advanced KNIME Analytics Platform Course and/or use KNIME on a regular basis.

With our 'Onsite Training & Summit Pass' you are able to attend 1 of 4 training sessions on Day 1 of the Summit.
You must select the course of your choice during the online registration.

 

TRAINING 1:   10:00AM - 5:30PM

This course is designed for those who are just starting their data analytics journey with KNIME Analytics Platform Version 5. It starts with a detailed introduction of KNIME Analytics Platform - from downloading it through to navigating the user interface. 

The course focuses on processing data from different sources and presenting insights in various forms. The course dives into data cleaning and aggregation, using methods such as advanced filtering, concatenating, joining, pivoting, and grouping. In addition, the course also covers topics such as data visualization, dashboards, and reporting to showcase findings from your data. With all of this, you will be able to get your data into the right shape to generate insights quickly.

This is an in-person instructor-led course run by our KNIME data scientists and solution engineers.

What level of KNIME experience is needed for this course?

None! We’ll start right from the beginning and teach you everything you need to know to get your data processing done with KNIME Analytics Platform.

 

TRAINING 2:   10:00AM - 5:30PM

This course builds on the [L1-AP] Data Literacy with KNIME Analytics Platform - Basics by introducing advanced concepts for building and automating workflows. 

This course covers topics for controlling node settings and automating workflow execution. You will learn concepts such as flow variables, loops, switches, and how to catch errors. In addition, you will learn how to handle date and time data, how to create advanced dashboards, and how to process data within a database. 

Moreover, this course introduces basic concepts of data engineering. You will learn different types of data, structured, semi-structured and unstructured, as well as different sources of data. There will be examples and exercises showcasing how to handle such data.

This is an in-person instructor-led course run by our KNIME data scientists and solution engineers.

What level of KNIME experience is needed for this course?

You should already know how to build workflows using KNIME Analytics Platform. This course doesn’t provide an introduction to KNIME Analytics Platform - it focuses on more advanced concepts of automating and building workflows.

 

TRAINING 3:   10:00AM - 5:30PM

You have created a data pipeline with KNIME Analytics Platform. But how to put it into production so as to make the data available to end users? In this course, we will show you how to use KNIME Software to test and deploy a data transformation workflow, automate its deployment and enable the subsequent data monitoring, and maintenance. 

We will consider a use case of creating a data pipeline to manage the orders data for a restaurant franchise that receives data from various branches, demonstrate how to deploy the data transformation workflow manually or automatically, and how to schedule and trigger the execution of data pipelines in a production environment.

First, you will learn how to prepare a data transformation workflow for deployment. Then you will be introduced to KNIME Business Hub and will learn how to deploy a data pipeline as a scheduled or triggered execution. Next, you will learn types of data pipeline - ETL and ELT, and how to use the Continuous Deployment for Data Science (CDDS) extension framework to enable automated deployment on KNIME Business Hub. Finally, you will learn about the best practices to productionize data pipelines: the principles of data governance - quality, security and cataloging, orchestration and performance optimization. 

This is an in-person instructor-led course run by our KNIME data scientists and solution engineers.

What level of KNIME experience is needed for this course?

You should already know how to build workflows, access databases and files, use flow variables and components in KNIME Analytics Platform. We recommend taking L1-AP and L2-DE courses or equivalent before attending this course.

 

TRAINING 4:   10:00AM - 5:30PM

This course focuses on how to use KNIME Analytics Platform for data engineering and how to apply best practices when building data processing pipelines.

Learn the concepts behind connecting to multiple data sources, the methods for data anonymization, and advanced database topics. Be introduced to the Apache Hadoop ecosystem and find out how to handle big data with the Apache Spark integration. Finally, learn how to build and orchestrate modular workflows.

Put your knowledge into practice with hands-on exercises to build and orchestrate two applications: first, extract, validate, transform, blend, anonymize, and load the customer data to a database; second, use Spark to access, impute missing values, and aggregate the website usage data. 

This is an in-person instructor-led course run by our KNIME data scientists and solution engineers.

What level of KNIME experience is needed for this course?

This course doesn’t provide a detailed introduction to KNIME Analytics Platform. You should be competent in using KNIME Analytics Platform. We expect that you have already built KNIME workflows and are aware of the workflow control concepts such as flow variables, loops, switches, and error handling. We recommend taking this course after obtaining the L1 and L2 KNIME proficiency or equivalent.

Onsite and Online Sessions

What else to expect

As an onsite ticket holder, you have access to multiple breakout sessions and workshops.
Meet face to face with other data experts, connect personally with the presenters, and enjoy in-depth learning.
Training 2 - small

WORKSHOPS

Onsite Only

Workshops will run throughout the morning coffee break on Day 2 and Day 3 of the Summit. There will be two (2) workshops to choose from each day.

Tues 16

  • Workshop 1: How to build Data Apps
  • Workshop 2: Data strategies for Data Engineers

Wed 17

  • Workshop 3: Gen Ai
  • Workshop 4: From Excel to Excellence: enhancing Excel with KNIME

Join any workshop you like with no need to reserve a spot in advance. 

Women in Tech - small

BIRDS OF A FEATHER SESSIONS

Onsite Only

Visit one of 3 'Birds of a Feather' sessions during lunch breaks. Choose a topic that interests you, and join the conversation over lunch!

Birds of a Feather sessions will be held on both Day 2 & Day 3 of the Summit and hosted by a KNIME representative.

Topics are:

  • Certified Trainers
    - with Aline Bessa 
  • Building a Community at Customers - with Scott Fincher
  • Aspiring and Real Data Connect Organizers - with Shantanu Tyagi

 

Partner expo - small

PARTNER EXHIBITION

Onsite Only

Visit our exhibition area to meet and discuss your specific use cases with our expert partners.

Partner Exhibition will be open on both Day 2 & 3 of the Summit in the Ballroom Foyer.

keyvisual-building-the-right-data-pipeline-for-drug-discovery

ONLINE BREAKOUTS

Virtual ticket holders

Join the online breakout rooms during breaks to meet the KNIME team and chat with other online attendees.

Breakouts will be open on both  Day 2 & 3 of the Summit.

Sessions will be announced on the Event Page, 1 week out from the event. Use your access link in the ticket confirmation email, or calendar invite to access the page.

Summit Passes

Onsite Training + Summit Pass
 
 
$650
 
 
3 Day access to the Summit

April 15 - 17 I Attend in-person Monday, Tuesday & Wednesday.

 

Ticket Inclusions:

  • Full day training ~ Day 1
  • Keynote
  • Workshops
  • Presentations
  • Breakout sessions
  • Partner exhibition access
  • Welcome reception ~ Day 1
  • Offsite reception ~ Day 2
  • In-person networking
  • Post event access to recordings

    ** All meals included


Full agenda coming soon

Onsite Summit Pass

 
$350
 
 
2 Day access to the Summit

April 16 - 17 I Attend in-person Tuesday & Wednesday.

 

Ticket Inclusions:

  • Keynote
  • Workshops
  • Presentations
  • Breakout sessions
  • Partner exhibition access
  • Welcome reception ~ Day 1
  • Offsite reception ~ Day 2
  • In-person networking
  • Post event access to recordings

    ** All meals included

Full agenda coming soon

Virtual Summit Pass
 
 
FREE
 
 
2 Day access to the Summit Online

April 16 - 17 I Live online streaming Tuesday & Wednesday.

 

Ticket Inclusions:

  • Keynote
  • Workshops
  • Presentations
  • Breakout sessions
  • Post event access to recordings

 

 

 

Full agenda coming soon


You may need to know

Frequently Asked Questions

 

Why should I consider to join onsite?

Joining the KNIME Summit is a great way to meet your peers, stay up to date on the latest software news and learn about inspiring KNIME stories. Take an instructor-led-training, get all your questions answered by the workflow doctor, and exchange ideas with the KNIME team and community.

Will the sessions be recorded?

Yes, we will be recording all sessions. Recordings and materials will be sent to all registrants (virtual and onsite) a few days after the Summit. Please register to get access. 

Can I purchase multiple tickets?

There is a limit of 5 tickets per registrant. Group discounts are available for larger numbers. Please email us for assistance: events@knime.com

In which language will the event be held?

The entire KNIME Spring Summit will be held in English.

Where will the event take place?

The event will take place at the AT&T Hotel and Conference Center in Austin, TX. You can book a hotel room here on our special rate.