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Where the global AI community unites to build the future.

Get ready to deepen your expertise, forge powerful connections, and stay at the absolute forefront of artificial intelligence. ODSC AI East is returning to Boston, MA at the Hynes Convention Center, April 28–30, for three days dedicated to practical, hands-on learning and community growth. And/OR you may join Virtual Conference. More details here - https://odsc.ai/east/

First Speakers Announcement

• Adam Tauman Kalai, Safety and Ethics Researcher, OpenAI
• Jonathan Frankle, Chief AI Scientist, Databricks
• Amy Hodler, Executive Director, GraphGeeks.org
• David Campbell, Head of AI Security, Scale AI
• Ben Armstrong\, PhD\, Executive Director \| Co-Lead\, Work of the Future\, MIT
• Ari Morcos, PhD, CEO and Co-founder, Datology AI
• Sydney Runkle, Software Engineer, LangChain
• Noah Giansiracusa, PhD, Assoc. Prof. of Math and DS, Bentley University
• Karen Zhou, Member of Technical Staff, Anthropic
• Joseph Fuller\, Prof. \| Co-head\, Future of Work Project\, Harvard Business School
• Denise Gosnell, Co-Founder & CEO, Data Driven Intuition
• Rajiv Shah, PhD, Chief Evangelist, Contextual AI
• Claire (Yunzhu) Zhao\, Director\, Group Lead \| AI/ML\, AQDS\, Pfizer
• David Hoyle, PhD Research Data Science Specialist, dunnhumby
• Dr. Denis Garagić, Chief Technology Officer & Co-founder, Palladyne AI
• Jeremiah Lowin, Founder & CEO, Prefect
• Veronika Durgin, VP of Data
• Xiong Liu Director, Data Science and AI, Novartis
• Mohammad Soltanieh-ha, PhD, Clinical Assistant Professor, Boston University

This is more than just a conference; it’s the essential event for data science practitioners, AI builders, technical leaders, and anyone looking to pivot into an AI-driven career. With 300+ hours of content from 250+ expert speakers, you'll gain job-ready skills and strategic insights you can implement immediately.

Why You Need to Be Here: Learning and Value

Technical Tracks: Data Engineering \| Physical AI \| AI for BioPharma & Health \| LLMs\, GenAI & RAG \| Agentic AI & Workflow Automation \| Keynotes & Industry Leadership \| Data Science & Machine Learning & MLOps \| AI Engineering & AIOps

Non-Technical Tracks: AI Strategy \| AI Risk & Governance \| Agentic AI for Enterprise \| AI Products & Innovation \| AI & Future of work \| Executive Track \| AI Founder Track

At ODSC AI East, we prioritize tangible value and immersive learning, ensuring you walk away certified and skilled. Our expansive agenda is packed with cutting-edge workshops and deep-dive tutorials across the most in-demand domains:

• Hands-On Training: Master crucial skills in LLMs, Generative AI & RAG, AI Engineering & MLOps, Data Science, and Machine Learning with expert-led, hands-on sessions.
• Focused Tracks: Explore specialized content in Agentic AI & Workflow Automation, Data Engineering, and AI for Robotics.
• Learn from Engineers Who Ship: Our speakers are the industry's top practitioners and researchers, renowned for bringing real-world innovations and strategies to the stage.

Beyond the Talks: Our Expanded Community Events

The true value of ODSC AI East is the opportunity to connect and collaborate. Your pass unlocks a rich ecosystem of co-located events and unique networking opportunities designed for every career level:

• AI X Leadership Summit (Co-located): A curated forum for executives, business leaders, and technical managers to gain practical insights on shaping, governing, and scaling their organization’s AI strategy.
• AI Mini-Bootcamp: Kickstart your journey or reinforce fundamentals with our intensive, pre-conference AI training and certification tracks.
• AI Expo & Demo Hall: Explore the latest advancements, witness live product demos, and meet technical experts from leading AI companies and innovative startups. This is the place to gain insight into build vs. buy decisions for enterprise AI solutions.
• Networking+ Activities & Events: Challenge yourself to grow your network at our dedicated events, including the Main Network Reception, targeted Lunch Meetups, and exclusive VIP Networking sessions, forging invaluable connections across the global community.

Join us in celebrating our community's pursuit of knowledge, inclusivity, and fairness as we work together to move the world of data science forward. Ready to build better AI? Find your perfect pass and secure your spot at ODSC AI East 2026 today!

Useful Links

• ​​Free access to more talks/trainings: Ai+ Training platform
• ​​ODSC blog: https://opendatascience.com/
• ​​Slack Channel: https://hubs.li/Q03SyZP80
• ​​Code of conduct: https://odsc.ai/code-of-conduct/

Summary Finding connections between data and the entities that they represent is a complex problem. Graph data models and the applications built on top of them are perfect for representing relationships and finding emergent structures in your information. In this episode Denise Gosnell and Matthias Broecheler discuss their recent book, the Practitioner’s Guide To Graph Data, including the fundamental principles that you need to know about graph structures, the current state of graph support in database engines, tooling, and query languages, as well as useful tips on potential pitfalls when putting them into production. This was an informative and enlightening conversation with two experts on graph data applications that will help you start on the right track in your own projects.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it? I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. Go to dataengineeringpodcast.com/97things to add your voice and share your hard-earned expertise. When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $60 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Today’s episode of the Data Engineering Podcast is sponsored by Datadog, a SaaS-based monitoring and analytics platform for cloud-scale infrastructure, applications, logs, and more. Datadog uses machine-learning based algorithms to detect errors and anomalies across your entire stack—which reduces the time it takes to detect and address outages and helps promote collaboration between Data Engineering, Operations, and the rest of the company. Go to dataengineeringpodcast.com/datadog today to start your free 14 day trial. If you start a trial and install Datadog’s agent, Datadog will send you a free T-shirt. You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data platforms. For more opportunities to stay up to date, gain new skills, and learn from your peers there are a growing number of virtual events that you can attend from the comfort and safety of your home. Go to dataengineeringpodcast.com/conferences to check out the upcoming events being offered by our partners and get registered today! Your host is Tobias Macey and today I’m interviewing Denise Gosnell and Matthias Broecheler about the recently published practitioner’s guide to graph data

Interview

Introduction How did you get involved in the area of data management? Can you start by explaining what your goals are for the Practitioner’s Guide To Graph Data?

What was your motivation for writing a book to address this topic?

What do you see as the driving force behind the growing popularity of graph technologies in recent years? What are some of the common use cases/applications of graph data and graph traversal algorithms?

What are the core elements of graph thinking that data teams need to be aware of to be effective in identifying those cases in their existing systems?

What are the fundamental principles of graph technologies that data engineers should be familiar with?

Wha

Graph data closes the gap between the way humans and computers view the world. While computers rely on static rows and columns of data, people navigate and reason about life through relationships. This practical guide demonstrates how graph data brings these two approaches together. By working with concepts from graph theory, database schema, distributed systems, and data analysis, you’ll arrive at a unique intersection known as graph thinking. Authors Denise Koessler Gosnell and Matthias Broecheler show data engineers, data scientists, and data analysts how to solve complex problems with graph databases. You’ll explore templates for building with graph technology, along with examples that demonstrate how teams think about graph data within an application. Build an example application architecture with relational and graph technologies Use graph technology to build a Customer 360 application, the most popular graph data pattern today Dive into hierarchical data and troubleshoot a new paradigm that comes from working with graph data Find paths in graph data and learn why your trust in different paths motivates and informs your preferences Use collaborative filtering to design a Netflix-inspired recommendation system

What is this book about? Written by an Access programmer with more than 10 years of VBA experience, this is the perfect guide for Access users who are ready to take their databases to the next level, or for programmers who are new to Access or VBA. Veteran Access developer Denise Gosnell shows readers the ins and outs of Access VBA and provides plenty of source code, and fully developed sample applications to guide you along the way. Not only do readers learn to build "stand-alone" desktop applications, but readers also learn how to integrate Access applications with Web Services, and SQL Server.