Sessions
Keynotes
Panels
Workshops
Talks
A Practical Guide to Robust Multimodal Machine Learning and Its Application in Education
Effective IAM: How Auto OTP Provides the Foundation for Zero Trust Security & Convenience
How to Break into Business Intelligence & Data Analytics
Integrating data science initiatives in business strategy for small businesses
Building scalable end-to-end deep learning pipelines in the cloud
End-to-End File Encryption in Browser with Open Source Penumbra
Hispanic Demographics basing on most recent 2020 Decennial Survey: by states and counties
Empowering Employment for Women in Tech with Artificial Intelligence?
Cloud Native and Headless BI is Here to Usher in the Future of Data Analytics
Schema Modeling Patterns and Best Practices for MongoDB
Demystifying the art of Business Intelligence and Data Analytics
Integrating and Visualizing Data to Make Better Decisions
Overcoming data infrastructure limitations with a new paradigm for machine learning
Columnar Storage + Python: Powering Modern Data Science and Analytics
Talk to Your Data: Query Your Data Lake with Amazon QuickSight Q
21st Century Machine Learning-based Data Analytics Driven by Social Media
Building Production Data Pipelines by using Test Driven Development and Pair Programming
Engineering a Consent Sandbox to Eliminate Annoying Pop-Ups and Dark Patterns
Measuring the Moving Parts of User Experience in Java/.NET applications
Is a Ransomware Attack in your Future? How to Prevent an Attack
Personalized By Design: How to unlock long term customer value with data
Using Streaming Data Pipelines in the Cloud to Achieve Success with Data Oriented Business Problems
Cryptographic speed, reliability & security
Leveraging big data to maximize value from rail and power infrastructure assets
Scaling sentiment: Using digital surveys to geo-target vaccine distribution in California
Too Much Drama and Horror Already: The COVID-19 Pandemic's Effects on What We Watch on TV
Keeping pace with data infrastructure so it doesn't outrun you
Creating and operating ML models from event-based data using feature stores and feature engines
Identifying opportunities and managing risks with impact and ESG data
Moving from a Monolithic Data Platform to a Distributed Data Mesh
Sparse models are fast models: Improving DNN inference performance by over 10X