The Data Day Texas 2022 Schedule

8:00 am

Registration and Morning Coffee (3rd Floor)

9:00 am

Opening Keynote Jonathan Mugan (DeUmbra) : A Path to Strong AI - 3rd Floor - Salon C

10:10 am

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NEW : Shirshanka Das : The Data Practitioner's Guide to Metadata - 3rd Floor - Salon C
Jike Chong / Yue Cathy Chang : For the overwhelmed data professionals: What to do when there is so much to do? - 3rd Floor - Salon A/B
Paige Roberts : Shortcut MLOps with In-Database Machine Learning - 3rd Floor - Salon D/E
Max De Marzi : Outrageous ideas for Graph Databases - 1st Floor - Room 104
Dave Bechberger : A gentle introduction to using graph neural networks on knowledge graphs - 1st Floor - Classroom 105
Heather Hedden : Introduction to Taxonomies for Data Scientists - 1st Floor - Classroom 106

11:00 am

Andy Petrella : What is Data Observability, and why should data teams consider it? - 3rd Floor - Salon A/B
Bob Van Luijt : Introduction to Vector Search Engines - 3rd Floor - Salon D/E
Amy Hodler / Michelle Yi : Relational Graphs Part I: Business Models Become the Program - 1st Floor - Room 101
Ryan Mitchell : What is Truth? - Strategies for managing semantic triples in large complex systems - 1st Floor - Classroom 104
Alexander Morrise : A 90 minute hands-on GNN Primer: Everything you wanted to know about Graph AI (but were too afraid to ask) - 1st Floor - Classroom 105
Heather Hedden : (continued) Introduction to Taxonomies for Data Scientists: Part 2 - 1st Floor - Classroom 106

11:50 am

NEW : Michael Hunger : Graph Database : Ask me anything - 3rd Floor - Salon A/B
Sean Robinson : History of Network Science(canceled) - 3rd Floor - Salon A/B
NEW : Ryan Michael : Unlocking time-based Machine Learning with a new paradigm for engineering features from event-based data - 3rd Floor - Salon D/E
Amy Hodler / Michelle Yi : Relational Graphs Part II: UN Demo of Composable Knowledge - 1st Floor - Room 101
Arthur Keen : Machine Learning, Semantics, and Knowledge Graphs - 1st Floor - Classroom 104
Alexander Morrise : (continued) A 90 minute hands-on GNN Primer: Everything you wanted to know about Graph AI (but were too afraid to ask) - 1st Floor - Classroom 105
Heather Hedden : (continued) Introduction to Taxonomies for Data Scientists: Part 3 - 1st Floor - Classroom 106

12:30 am

Buffett Lunch Served in the following locations
Salon C (3rd floor)
Graph Community Lunch / Meet and Greet - 1st Floor - Room 103
Semantic Community Lunch / Meet and Greet - 1st Floor - Room 116 (sponsored by Pool Party)
Data Science Community Lunch / Meet and Greet - 1st Floor - Room 108 (sponsored by Graphable)

1:20pm

Jike Chong / Yue Cathy Chang : Data Professional's Career: Techniques to Practice Rigor and Avoid Ten Mistakes - 3rd Floor - Salon A/B
Bivin Sadler : A Comparison of Deep Learning Versus Parametric Time Series Models - 3rd Floor - Salon D/E
Thorsten Liebig : Connecting the Dots in a Million Node Graph - 1st Floor - Room 101
Jans Aasman : Event Predictions with Machine Learning and Graph Neural Networks - 1st Floor - Classroom 104
Ying Ding : Fighting COVID-19 using Knowledge Graphs - 1st Floor - Classroom 105
Michael Uschold : Intro to Ontology - 1st Floor - Classroom 106

2:10pm

Elliott Cordo : Building a Modern Data Platform Using Advanced Redshift Topologies - 3rd Floor - Salon A/B
Paul Azunre : Business Transformers - Leveraging Transfer Learning for B2B Insights - 3rd Floor - Salon C
Chris Rossbach : Katana Graph Technical Foundations - 1st Floor - Salon D/E
Jórg Schad : It was the best of Graph, it was the worst of Graph - Choosing between Graph ML and Graph Analytics - 1st Floor - Classroom 104
David Hughes : Clinical trials exploration: surfacing a clinical application from a larger Bio-Pharma KnowledgeGraph(canceled) - 1st Floor - Classroom 105
Michael Uschold : (continued) Intro to Ontology - 1st Floor - Classroom 106

3:00pm

Kirk Marple : Unstructured Data Management: It's not just for your documents - 3rd Floor - Salon A/B
Michael Zelenetz : This Dashboard Should Have Been a Meeting - 3rd Floor - Salon D/E
Corey Lanum : Visual timeline analytics: applying concepts from graph theory to timeline and time series data - 3rd Floor - Salon C
Josh Shinavier : Announcing Hydra - 1st Floor - Classroom 104
Leo Meyerowich : Graph Intelligence - 1st Floor - Classroom 105
Boris Iordanov :Upper Ontologies - 1st Floor - Classroom 106

3:40pm

Afternoon Break
Open Bar - 3rd Floor - Salon C

4:20pm

Joey Jablonski : Approaches to Modern Data Governance - 3rd Floor - Salon C
Sachin Sharma : Graph Neural Networks with PyTorch - 1st Floor - Room 101
Heather Hedden : The Future of Taxonomy - 1st Floor - Classroom 104
Jonathan Mugan : RLlib for Deep Hierarchical Multiagent Reinforcement Learning - 1st Floor - Classroom 105
Satoru Hayasaka :Codeless Deep Learning with KNIME - 1st Floor - Classroom 106

5:10pm

NEW: Panel - Michael Uschold / Josh Shinavier / Ryan Wisnesky / Brandon Baylor / James Hansen : Scaling a knowledge graph when there is no consensus - 3rd Floor - Salon C
Sachin Sharma: (continued) Graph Neural Networks with PyTorch - 1st Floor - Room 101
Jonathan Mugan : (continued) RLlib for Deep Hierarchical Multiagent Reinforcement Learning - 1st Floor - Classroom 105
Satoru Hayasaka : (continued) Codeless Deep Learning with KNIME - 1st Floor - Classroom 106

6:00pm

Post Conference Happy Hour / Meet and Greet : Conference Center Courtyard