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
CareerBuilder
Hokuto Fujii
Yamaha Motor
Marcel Meyer
Siemens Healthineers
Michael Berthold
KNIME
Michael Richter
Hennessy Automobile Companies
Kate Bartkiewicz
digData
Dayanjan Shanaka Wijesinghe
VCU, School of Pharmacy
Fabiola Martina
Siemens Healthineers
Prof. Behrooz Davazdahemami
University of Wisconsin - Whitewater
Lee Fader
Congruence Therapeutics
Jerome Treboux
Forest Grove
Dakshitha Narendra Kiranakankanamage
ElectraNet
Selman Bayoglu
Kuveyt Türk Participation Bank
Ricardo Auerbach
BENTELER
Iris Adä
KNIME
VP Data & Analytics
Marcel Meyer
Siemens Healthineers
Michael Berthold
KNIME
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.
Kate Bartkiewicz
digData
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.
Dayanjan Shanaka Wijesinghe
VCU, School of Pharmacy
Fabiola Martina
Siemens Healthineers
Prof. Behrooz Davazdahemami
University of Wisconsin - Whitewater
Lee Fader
Congruence Therapeutics
Jerome Treboux
Forest Grove
Dakshitha Narendra Kiranakankanamage
ElectraNet
Selman Bayoglu
Kuveyt Türk Participation Bank
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.
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.
Previous companies who attended 2022/2023
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)
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.
You must select the course of your choice during the online registration.
- L1-AP | Data Literacy with KNIME Analytics Platform: Basics
- L2-DE | Data Engineering with KNIME Analytics Platform: Advanced
- L3-DE | Productionizing Data Pipelines
- L4-DE | Best Practices for Data Engineering
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
Meet face to face with other data experts, connect personally with the presenters, and enjoy in-depth learning.
- Workshops
- Birds of a Feather
- Partner Exhibition
- Online Breakouts
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.
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 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.
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
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 shown above
Onsite Summit Pass
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 shown above
April 16 - 17 I Live online streaming Tuesday & Wednesday.
Ticket Inclusions:
- Keynote
- Presentations
- Breakout sessions
- Post event access to recordings
Access to the full online agenda will be available 1 week prior to event - via your access link
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.