Agenda

Structured Streaming with Lakehouse

Training

Foundations of Scalable Natural Language Processing

Training

Databricks Platform Administration

Training

Apache Spark Programming

Training

Introduction to SQL Analytics on Lakehouse

Training

Data Engineering with Lakehouse

Training

Scaling Deep Learning with TensorFlow and Apache Spark

Training

Software Engineering Best Practices for Data & AI

Training

Scaling Machine Learning Pipelines with Apache Spark

Training

Performance Tuning on Apache Spark

Training

Machine Learning in Production

Training

Associate Developer Prep + Certification Voucher

Training

Introduction to Reinforcement Learning

Training

Databricks Lakehouse Overview

Training

Lakehouse with Delta Lake Deep Dive

Training

Security Threat Detection with Databricks

Training

Phar Data Platform: From the Lakehouse Paradigm to the Reality

Marc Planagumà

Data Engineering and Data Architecture

Scaling Machine Learning Pipelines with Apache Spark

Training

Scaling Deep Learning with TensorFlow and Apache Spark

Training

Databricks Platform Administration

Training

Foundations of Scalable Natural Language Processing

Training

Associate Developer Prep + Certification Voucher

Training

Introduction to SQL Analytics on Lakehouse

Training

Software Engineering Best Practices for Data & AI

Training

Lakehouse with Delta Lake Deep Dive

Training

Databricks Lakehouse Overview

Training

Security Threat Detection with Databricks

Training

Machine Learning in Production

Training

Structured Streaming with Lakehouse

Training

Scaling Deep Learning with TensorFlow and Apache Spark

Training

Associate Developer Prep + Certification Voucher

Training

Software Engineering Best Practices for Data & AI

Training

Databricks Platform Administration

Training

Scaling Machine Learning Pipelines with Apache Spark

Training

Foundations of Scalable Natural Language Processing

Training

Apache Spark Programming

Training

Data Engineering with Lakehouse

Training

Introduction to SQL Analytics on Lakehouse

Training

Performance Tuning on Apache Spark

Training

Introduction to Reinforcement Learning

Training

Databricks Lakehouse Overview

Training

Lakehouse with Delta Lake Deep Dive

Training

Security Threat Detection with Databricks

Training

Scaling Deep Learning with TensorFlow and Apache Spark

Training

Foundations of Scalable Natural Language Processing

Training

Databricks Platform Administration

Training

Associate Developer Prep + Certification Voucher

Training

Introduction to SQL Analytics on Lakehouse

Training

Software Engineering Best Practices for Data & AI

Training

Scaling Machine Learning Pipelines with Apache Spark

Training

Lakehouse with Delta Lake Deep Dive

Training

Databricks Lakehouse Overview

Training

Security Threat Detection with Databricks

Training

Building Data Quality pipelines with Apache Spark and Delta Lake

Darren Fuller, Elastacloud Ltd | Sandy May, Elastacloud

Data Engineering and Data Architecture

Creating an 86,000 Hour Speech Dataset with Apache Spark and TPUs

Daniel Galvez, MLCommons

Data Science, Deep Learning and ML

Data Distribution and Ordering for Efficient Data Source V2

Anton Okolnychyi, Apple

Apache Spark Internals and Best Practices

Scaling AI At H&M

Bjorn Hertzberg, H&M

AI Use Cases

Becoming a Data Driven Organization with Modern Lakehouse

Vini Jaiswal, Databricks

SQL Analytics and BI

RWE & Patient Analytics Leveraging Databricks – A Use Case

Harini Gopalakrishnan, Sanofi | Martin Longpre, Sanofi

Industry and Business Use Cases

Catch Me If You Can: Keeping Up With ML Models in Production

Bora Uyumazturk, Viaduct | Shreya Shankar

Data Science, Deep Learning and ML

Customer Experience at Disney+ Through Data Perspective

Rekha Bachwani, Disney+ | Martin Zapletal, Disney+

Data Engineering and Data Architecture

KFServing, Model Monitoring with Apache Spark and a Feature Store

Jim Dowling, Logical Clocks AB | Javier de la Rúa Martínez, Logical Clocks

Open Source Data and ML Tools

Building Data Science into Organizations: Field Experience

Joseph Bradley, Databricks

Data Science, Deep Learning and ML

Scaling Online ML Predictions At DoorDash

Hien Luu, DoorDash

Data Science, Deep Learning and ML

Delta Lake Streaming: Under the Hood

Shasidhar Eranti, Databricks

Data Engineering and Data Architecture

Detecting Anomalous Behavior with Surveillance​ Analytics​

Vinamre Dhar, Kushagramati Analytics | Rishan Sanjay, Kushagramati Analytics

AI Use Cases

Graph-Powered Machine Learning

Jorg Schad, ArangoDB

Data Science, Deep Learning and ML

Magnet Shuffle Service: Push-based Shuffle at LinkedIn

Chandni Singh, LinkedIn | Min Shen, LinkedIn

Data and ML Research

DevOps for Databricks

Anna Wykes, Advancing Analytics

Databricks Production Use Cases

Data Security at Scale through Spark and Parquet Encryption

Gidon Gershinsky, Apple | Tim Perelmutov, Apple

Data Engineering and Data Architecture

Funnel Analysis with Apache Spark and Druid

Etti Gur, Nielsen | Itai Yaffe, Imply

Open Source Data and ML Tools

Keeping Identity Graphs In Sync With Apache Spark

Ruben Berenguel, Hybrid Theory

Industry and Business Use Cases

Automating Data Quality Processes at Reckitt

Richard Chadwick | Karol Sawicz, Reckitt

Data Engineering and Data Architecture

Creating Reusable Geospatial Pipelines

Dan Corbiani, Pacific Northwest National Lab

Data Science, Deep Learning and ML

Experimentation to Industrialization: Implementing MLOps

Al McEwan, Thorogood Associates | Deb Lee, Thorogood Associates

Data Science, Deep Learning and ML

Monitor Apache Spark 3 on Kubernetes using Metrics and Plugins

Luca Canali, CERN

Apache Spark Internals and Best Practices

BOTS TESTING BOTS: From manual to automated testing for conversational AI

Christoph Börner, Botium GmbH

AI Use Cases

SCOR’s NonLife Risk Modelling (NORMA) on Databricks Apache Spark

Sahand Razzaghi, SCOR | Luca Valentino, SCOR

Industry and Business Use Cases

Commercializing Alternative Data

Jay Bhankharia, S&P Global | Srinivasa Podugu, S&P Global

Industry and Business Use Cases

Image Processing on Delta Lake

Jason Robey, Databricks | Rohit Gopal, Databricks

Open Source Data and ML Tools

Productionizing Machine Learning in Health and Wellness Mark

Genna Gliner

Data Science, Deep Learning and ML

How We Scaled Bert To Serve 1+ Billion Daily Requests on CPU

Quoc Le, Roblox | Kip Kaehler, Roblox

Data Science, Deep Learning and ML

Enabling Vectorized Engine in Apache Spark

Kazuaki Ishizaki, IBM

Apache Spark Internals and Best Practices

Advanced Natural Language Processing with Apache Spark NLP

David Talby, John Snow Labs

AI Use Cases

CI/CD in MLOps – Implementing a Framework for Self-Service Everything

Cara Phillips, Artis Consulting | Wesly Clark, J.B. Hunt

Data Science, Deep Learning and ML

Code Once Use Often with Declarative Data Pipelines

Anthony Awuley, Flashfood | Carter Kilgour, Flashfood

Data Engineering and Data Architecture

Northwestern Mutual Journey – Transform BI Space to Cloud

Madhu Kotian, Northwestern Mutual

SQL Analytics and BI

Auto-Train a Time-Series Forecast Model With AML + ADB

Moritz Steller, Microsoft

Data Science, Deep Learning and ML

Bring Your Own Container: Using Docker Images In Production

Harin Sanghirun, Condé Nast | Max Cantor, Condé Nast

Databricks Production Use Cases

Building End-to-End Delta Pipelines on GCP

Himanish Kushary, Databricks | Molly Nagamuthu, Databricks

Data Engineering and Data Architecture

FrugalML: Using ML APIs More Accurately and Cheaply

Lingjiao Chen, Stanford University

AI Use Cases

Massive Data Processing in Adobe Using Delta Lake

Yeshwanth Vijayakumar, Adobe, Inc.

Databricks Production Use Cases

Migration to Apache Spark 3 – Lessons From the Field

Gagandeep Singh Chawla, Databricks | Prashanth Babu, Databricks

Apache Spark Internals and Best Practices

Accelerate Data Science Initiatives: Databricks & Privacera

Don Bosco Durai, Privacera

SQL Analytics and BI

The Critical Missing Component in the Production ML Stack

Alessya Visnjic, WhyLabs, Inc.

Data Science, Deep Learning and ML

PandasUDFs: One Weird Trick to Scaled Ensembles

Paul Anzel, H-E-B

Data Science, Deep Learning and ML

Predicting Optimal Parallelism for Data Analytics

Rathijit Sen, Microsoft | Vishal Rohra, Microsoft

Data and ML Research

Improving Power Grid Reliability Using IoT Analytics

Jim Brown, Neudesic | Minjie Yu, DTE Energy

Industry and Business Use Cases

Modern Config Driven ELT Framework for Building a Data Lake

Fred Kimball, Northwestern Mutual

Data Engineering and Data Architecture

Empowering Zillow’s Developers with Self-Service ETL

Derek Gorthy, Zillow | Yuan Feng, Zillow

Data Engineering and Data Architecture

Tensors Are All You Need: Faster Inference with Hummingbird

Karla Saur, Microsoft | Matteo Interlandi, Microsoft

Data Science, Deep Learning and ML

Play Head Time Analysis On OTT Video At Scale

Adam Liu, Conviva | Biplab Chattopadhyay, Conviva

Industry and Business Use Cases

FlorenceAI: Reinventing Data Science at Humana

David Mack, Humana, Inc.

Data Science, Deep Learning and ML

Model Monitoring at Scale with Apache Spark and Verta

Manasi Vartak, Verta Inc

Data Science, Deep Learning and ML

Productionalizing Machine Learning Solutions with Effective Tracking, Monitoring, and Management

Sumanth Venkatasubbaiah, Intuit | Pankaj Rastogi, Intuit

Data Science, Deep Learning and ML

Building Source of Truth Place Data at Scale

Nan Zhu, SafeGraph

Data Engineering and Data Architecture

Koalas: Does Koalas Work Well or Not?

Takuya Ueshin, Databricks | Xinrong Meng, Databricks

Open Source Data and ML Tools

Object Detection with Transformers

Liam Li, Determined AI

Data Science, Deep Learning and ML

Accelerate Analytics On Databricks

Jeff King, Microsoft | Paul Scott-Murphy, WANdisco

AI Use Cases

How Adobe uses Structured Streaming at Scale

Yeshwanth Vijayakumar, Adobe, Inc.

Data Engineering and Data Architecture

Drug Repurposing using Deep Learning on Knowledge Graphs

Alexander Thomas, Wisecube AI | Vishnu Vettrivel, Wisecube AI

AI Use Cases

Extending Machine Learning Algorithms with PySpark

Karen Feng, Databricks | Kiavash Kianfar, Databricks

Data and ML Research

Delivering Insights from 20M+ Smart Homes with 500M+ devices

SQL Analytics and BI

Scaling and Modernizing Data Platform with Databricks

Richa Singhal, Atlassian | Esha Shah, Atlassian

Databricks Production Use Cases

AI Data Acquisition and Governance: Considerations for Success

Kirsten Gokay, Appen

AI Use Cases

A Collaborative Data Science Development Workflow

Nicholas Hale, Trillion Technology Solutions

Data Science, Deep Learning and ML

Large Scale Geospatial Indexing and Analysis on Apache Spark

Felix Cheung, SafeGraph

Open Source Data and ML Tools

Advanced Model Comparison and Automated Deployment Using ML

Charu Kalra, T-Mobile | Connor McCambridge, T-Mobile

Data Science, Deep Learning and ML

AI-Driven Personalized Email Marketing

Xi Liang, Endeavour Drinks

Industry and Business Use Cases

Automated Metadata Management in Data Lake – A CI/CD Driven Approach

Josh Reilly, Northwestern Mutual | Keyuri Shah

Data Engineering and Data Architecture

Wizard Driven AI Anomaly Detection with Databricks in Azure

Naomi Kaduwela, Kavi Global | Rajesh Inbasekaran, Kavi Global

Data Science, Deep Learning and ML

Analytics-Enabled Experiences: The New Secret Weapon

Jorge Lozano, Steelcase | Kevin Tian, Steelcase

Data Science, Deep Learning and ML

Managing Millions of Tests Using Databricks

Yin Huai, Databricks

Databricks Production Use Cases

A High Performance Mutable Engagement Activity Delta Lake

Heng Zhang, Salesforce | Zhidong Ke, Salesforce

Data Engineering and Data Architecture

Offer Recommendation System with Apache Spark at Burger King

Kai Huang, Intel Corporation | Luyang Wang, Burger King Corporation

AI Use Cases

Semantic Image Logging Using Approximate Statistics & MLflow

Leandro Almeida, Whylabs

Open Source Data and ML Tools

Consolidating MLOps at One of Europe’s Biggest Airports

Floris Hoogenboom, Royal Schiphol Group | Sebastiaan Grasdijk, Royal Schiphol Group

Data Science, Deep Learning and ML

Choose Your Weapon: Comparing Spark on FPGAs vs GPUs

Roop Ganguly, Bigstream Solutions Inc

Apache Spark Internals and Best Practices

Productionzing ML Model Using MLflow Model Serving

Nitin Raj Soundararajan, Cognizant Worldwide Limited | Nagaraj Sengodan, HCL Technologies

Data Science, Deep Learning and ML

Role of Data Accessibility During Pandemic

Vini Jaiswal, Databricks | Isaac Lee, Carnegie Mellon University

Open Source Data and ML Tools

Getting Started with Databricks SQL Analytics

Simon Whiteley, Advancing Analytics

SQL Analytics and BI

Bootstrapping of PySpark Models for Factorial A/B Tests

Ondrej Havlicek, DataSentics

Data Science, Deep Learning and ML

Structured Streaming Use-Cases at Apple

Kristine Guo, Apple | Liang-Chi Hsieh, Apple

Apache Spark Internals and Best Practices

Anomaly Detection at Scale!

Opher Dubrovsky, Nielsen | Max Peres, Nielsen

Data Science, Deep Learning and ML

Bridging the Completeness of Big Data on Databricks

Chao Yang, Verisk | Yanyan Wu, Verisk

Data Engineering and Data Architecture

Modelling Customer Lifetime Revenue for Subscription Business

Rajkumar Kaliyaperumal, Conde Nast | Leeladhar Nagineni, Condé Nast

Industry and Business Use Cases

YOLO with Data-Driven Software

Brooke Wenig, Databricks | Tim Hunter, ABN AMRO

Open Source Data and ML Tools

From Chatbots to Augmented Conversational Assistants

Frederic Jacquet, Talan | Lao-dja Songdou Tchala, Talan

AI Use Cases

Drifting Away: Testing ML Models in Production

Chengyin Eng, Databricks | Niall Turbitt, Databricks

Data Science, Deep Learning and ML

Building A Product Assortment Recommendation Engine

Ethan Dubois | Justin Morse, Anheuser Busch

Data Science, Deep Learning and ML

Unified MLOps: Feature Stores & Model Deployment

Jack Ploshnick, Splice Machine | Monte Zweben, Splice Machine

Open Source Data and ML Tools

ChakraView – A 360° Approach to Data Quality

Keerthika Thiyagarajan, Flipkart | Shankar Manian, Flipkart

Data Engineering and Data Architecture

Portable UDFs : Write Once, Run Anywhere

Tejas Patil, Facebook

Apache Spark Internals and Best Practices

Empowering Real Time Patient Care Through Spark Streaming

Arnav Chaudhary, Takeda

Databricks Production Use Cases

How Machine Learning and AI Can Support the Fight Against COVID-19

Dmitry Soshnikov, Microsoft | Francesca Lazzeri, Microsoft

Data Science, Deep Learning and ML

Accelerating Data Ingestion with Databricks Autoloader

Simon Whiteley, Advancing Analytics

Data Engineering and Data Architecture

The Rise of ZStandard: Apache Spark/Parquet/ORC/Avro

Dongjoon Hyun, Apple | Pang Wu, Apple

Apache Spark Internals and Best Practices

Considerations for Data Access in the Lakehouse

Zachary Friedman, Immuta

SQL Analytics and BI

Conversational AI with Transformer Models

Rajesh Shreedhar Bhat, Walmart Global Tech India | Dinesh Ladi, Walmart Global Tech India

AI Use Cases

Speed up UDFs with GPUs using the RAPIDS Accelerator

Jason Lowe, NVIDIA

Open Source Data and ML Tools

Tale of Scaling Zeus to Petabytes of Shuffle Data @Uber

Mayank Bansal, Uber Inc

Apache Spark Internals and Best Practices

Growing the Delta Ecosystem to Rust and Python with Delta-RS

R Tyler Croy, Scribd

Open Source Data and ML Tools

Credit Card Fraud Detection Using ML In Databricks

Badrish Davay, Capital One | Neil Allen, Capital One

Data Science, Deep Learning and ML

Modernize Your Analytics Workloads for Apache Spark 3.0 and Beyond

William Benton, NVIDIA

Apache Spark Internals and Best Practices

Scaling and Unifying SciKit Learn and Apache Spark Pipelines

Raghu Ganti, IBM Research

Data Science, Deep Learning and ML

Importance of ML Reproducibility & Applications with MLfLow

Gray Gwizdz, Databricks | Mary Grace Moesta, Databricks

Data Science, Deep Learning and ML

Building the Artificially Intelligent Enterprise

Mike Ferguson, Intelligent Business Strategies

Data Engineering and Data Architecture

How Databricks Leverages Auto Loader to Ingest Millions of Files an Hour

Pranav Anand, Databricks

Data Engineering and Data Architecture

Data Discovery at Databricks with Amundsen

Tao Feng, Databricks | Tianru Zhou, Databricks

Open Source Data and ML Tools

Entity Resolution Using Patient Records at CMMI

Brett Luskin, NewWave

Data Engineering and Data Architecture

MLflow Model Serving

Andre Mesarovic, Databricks

Data Science, Deep Learning and ML

Databricks: A Tool That Empowers You To Do More With Data

Francois Callewaert, Databricks

Data Science, Deep Learning and ML

Building Lakehouses on Delta Lake with SQL Analytics Primer

Franco Patano, Databricks

SQL Analytics and BI

Architect’s Open-Source Guide for a Data Mesh Architecture

Lena Hall, Microsoft

Data Engineering and Data Architecture

Accelerate Your ML Pipeline with AutoML and MLflow

Elena Boiarskaia, H2O.ai | Eric Gudgion, H2O.ai

Data Science, Deep Learning and ML

Democratizing Data Quality Through a Centralized Platform

Yuliana Havryshchuk, Zillow | Smit Shah, Zillow

Data Engineering and Data Architecture

Video Analytics At Scale: DL, CV, ML On Databricks Platform

Claudiu Barbura, Blueprint Technologies

Data Science, Deep Learning and ML

Migrating ETL Workflow to Apache Spark at Scale in Pinterest

Daniel Dai, Pinterest | Zirui Li, Pinterest

Data Engineering and Data Architecture

Project Zen: Making Data Science Easier in PySpark

Hyukjin Kwon, Databricks | Haejoon Lee, Databricks

Apache Spark Internals and Best Practices

How to use Apache TVM to optimize your ML models

Sameer Farooqui, OctoML

Data Science, Deep Learning and ML

Best Practices for Enabling Speculative Execution on Large Scale Platforms

Venkata Krishnan Sowrirajan, LinkedIn | Ron Hu, LinkedIn

Apache Spark Internals and Best Practices

Jeeves Grows Up: An AI Chatbot for Performance and Quality

Shivnath Babu, Unravel Data Systems/Duke University

AI Use Cases

Efficient Distributed Hyperparameter Tuning with Apache Spark

Viswesh Periyasamy, Databricks

Apache Spark Internals and Best Practices

Machine Learning CI/CD for Email Attack Detection

Jeshua Bratman, Abnormal Security | Justin Young, Abnormal Security

Data Science, Deep Learning and ML

Modularized ETL Writing with Apache Spark

Neelesh Salian, Stitch Fix

Data Engineering and Data Architecture

Building an ML Platform with Ray and MLflow

Amog Kamsetty, Anyscale | Archit Kulkarni, Anyscale

Open Source Data and ML Tools

Stage Level Scheduling Improving Big Data and AI Integration

Thomas Graves, NVIDIA

Apache Spark Internals and Best Practices

Degrading Performance? You Might be Suffering From the Small Files Syndrome

Adi Polak, Microsoft

Data Engineering and Data Architecture

Intuitive & Scalable Hyperparameter Tuning with Apache Spark + Fugue

Han Wang, Lyft Inc.

Data Science, Deep Learning and ML

Misusing MLflow To Help Deduplicate Data At Scale

Robin Oliva-Kraft, Intuit | Maya Livshits, Intuit

Databricks Production Use Cases

Scaling Privacy in a Spark Ecosystem

Aaron Colcord, Northwestern Mutual | Don Bosco Durai, Privacera

Industry and Business Use Cases

Effective AIOps with Open Source Software in a Week

Keith Andre Kroculick, Wells Fargo | Murali Kaundinya, Wells Fargo

AI Use Cases

The Rise of Vector Data

Edo Liberty, Pinecone

Data Engineering and Data Architecture

How We Optimize Spark SQL Jobs With parallel and sync IO

Jun Guo, Bytedance

Apache Spark Internals and Best Practices

Manipulating Geospatial Data at Massive Scale

Charcey Petersen, John Deere | Christopher Hicks, John Deere

Data Engineering and Data Architecture

From Vaccine Management to ICU Planning: How CRISP Unlocked the Power of Data During a Pandemic

Industry and Business Use Cases

Build Large-Scale Data Analytics and AI Pipeline Using RayDP

Carson Wang, Intel | Xianyang Liu, Intel

Data Science, Deep Learning and ML

Rethinking Feature Stores

Willem Pienaar, Tecton | Mike Del Balso

Data Science, Deep Learning and ML

Configuration Driven Reporting On Large Dataset Using Apache Spark

Arvind Das, american express | Zheng Gu, american express

Data Engineering and Data Architecture

MLCommons: Better ML for Everyone

David Kanter, MLCommons

Open Source Data and ML Tools

Simplify Data Conversion from Apache Spark to Deep Learning

Liang Zhang, Databricks

Open Source Data and ML Tools

Advanced SQL For Data Scientists

Jean Joseph, Allied World

SQL Analytics and BI

Migrating Your Data Platform At a High Growth Startup

Carlos Gasperi, Abnormal Security

Databricks Production Use Cases

Deep Dive into the New Features of Apache Spark 3.1

Wenchen Fan, Databricks | Xiao Li, Databricks

Apache Spark Internals and Best Practices

Real-world Strategies for Debugging Machine Learning Systems

Patrick Hall, bnh.ai | The George Washington University

Data Science, Deep Learning and ML

Re-imagine Data Monitoring with whylogs and Spark

Andy Dang, Whylabs

Data Science, Deep Learning and ML

Why APM Is Not the Same As ML Monitoring

Cory Johannsen, Verta Inc

Data Science, Deep Learning and ML

Let’s Dumb-Proof Data Pipelines

Ganesh Chand, Databricks

Data Engineering and Data Architecture

Hyperspace for Delta Lake

Rahul Potharaju, Microsoft | Terry Kim, Microsoft | Eunjin Song, Microsoft

Open Source Data and ML Tools

High Volume, High Speed Data Pipeline for ML @ Scale

Sid Dixit, Amazon

Data Science, Deep Learning and ML

Architecting Agile Data Applications for Scale

Richard Garris, Databricks

Data Engineering and Data Architecture

Weekday Demand Sensing at Walmart

John Bowman, Walmart Labs

Industry and Business Use Cases

Scaling AutoML-Driven Anomaly Detection With Luminaire

Sayan Chakraborty, Zillow, Inc. | Smit Shah, Zillow

Open Source Data and ML Tools

A Practical Enterprise Feature Store on Delta Lake

Bryan Christian | Nathan Buesgens, Accenture

Data Engineering and Data Architecture

Large Scale Lakehouse Implementation Using Structured Streaming

Tomasz Magdanski, Asurion

SQL Analytics and BI

Infrastructure Agnostic Machine Learning Workload Deployment

Abi Akogun, MavenCode | Charles Adetiloye, MavenCode

Data Science, Deep Learning and ML

Efficient Large-Scale Language Model Training on GPU Clusters

Deepak Narayanan, Stanford University

Data and ML Research

Machine Learning with PyCaret

Moez Ali, PyCaret

Open Source Data and ML Tools

The Function, the Context, and the Data

Elijah Ben Izzy, Stitch Fix

Data Science, Deep Learning and ML

Towards Personalization in Global Digital Health

Africa Perianez, benshi.ai

Data Science, Deep Learning and ML

How to Build a ML Platform Efficiently using Open-source

Jean Machado, GetYourGuide | Theodore Meynard, GetYourGuide

Data Science, Deep Learning and ML

Raven: End-to-end Optimization of ML Prediction Queries

Konstantinos Karanasos, Microsoft | Kwanghyun Park, Microsoft

Data and ML Research

Hybrid Apache Spark Architecture with YARN and Kubernetes

Catalin Toda, Lyft Inc. | Rohit Menon, Lyft Inc.

Data Engineering and Data Architecture

Drug and Vaccine Discovery: Knowledge Graph + Apache Spark

John Hunter, GlaxoSmithKline

Data and ML Research

Comprehensive View on Intervals in Apache Spark 3.2

Maxim Gekk, Databricks

Apache Spark Internals and Best Practices

Automated Background Removal Using PyTorch

Oleksander Miroshnychenko, GlobalLogic | Simona Stolnicu, Levi9

Data Science, Deep Learning and ML

Giving Away The Keys To The Kingdom: Using Terraform To Automate Databricks

Hamilton Hord, Scribd | Serge Smertin, Databricks

Databricks Production Use Cases

Building the Foundations of an Intelligent, Event-Driven Data Platform at EFSA

David De Wilde, Delaware Consulting CVBA | Sebastiaan Leysen, delaware

Data Engineering and Data Architecture

NLP-Focused Applied ML at Scale for Global Fleet Analytics at ExxonMobil

Sumeet Trehan, ExxonMobil

Industry and Business Use Cases

SQL Analytics Powering Telemetry Analysis at Comcast

Suraj Nesamani, Comcast | Molly Nagamuthu, Databricks

SQL Analytics and BI

Redis + Apache Spark = Swiss Army Knife Meets Kitchen Sink

Yeshwanth Vijayakumar, Adobe, Inc.

Data Engineering and Data Architecture

A Fast, Interpretable Feature Importance Summary

James Thomas, Stanford University

Open Source Data and ML Tools

Sawtooth Windows for Feature Aggregations

Nikhil Simha, Airbnb

Data and ML Research

Processing Large Datasets for ADAS Applications using Apache Spark

Arvind Hosagrahara, MathWorks, Inc.

Data Science, Deep Learning and ML

Improving Apache Spark for Dynamic Allocation and Spot Instances

Holden Karau, Apple

Apache Spark Internals and Best Practices

Managing R&D Data on Parallel Compute Infrastructure

Andrew Brown, ZS Associates

Databricks Production Use Cases

Building a Data Science as a Service platform in Azure

Terry McCann, Advancing Analytics

Databricks Production Use Cases

Recommender-Based Transformers

Denis Rothman, Denis Rothman

AI Use Cases

Change Data Feed in Delta

Rahul Mahadev, Databricks | Itai Weiss, Databricks | Jose Torres, Databricks

Data Engineering and Data Architecture

Gender Prediction with Databricks AutoML Pipeline

Industry and Business Use Cases

Optimizing the Catalyst Optimizer for Complex Plans

Jianneng Li, Workday

Apache Spark Internals and Best Practices

Natural Language Query and Conversational Interface to Apache Spark

Anand Ranganathan, Unscrambl

SQL Analytics and BI

10 Things Learned Releasing Databricks Enterprise Wide

Jake Kulas, Western Governors University

Databricks Production Use Cases

Scaling your Data Pipelines with Apache Spark on Kubernetes

Rajesh Thallam, Google | Sougata Biswas, Google

Data Engineering and Data Architecture

Build Real-Time Applications with Databricks Streaming

Bennie Haelen, Insight Digital Innovation

Databricks Production Use Cases

Superworkflow of Graph Neural Networks with K8S and Fugue

Jintao Zhang, Square Inc.

Data Science, Deep Learning and ML

Fully Utilizing Spark for Data Validation

Kevin Kho, Prefect

Data Science, Deep Learning and ML

Automatic ICD-10 Code Assignment to Consultations

Joinal Ahmed, Halodoc Technologies | Nirav Kumar, Halodoc Technologies

Data and ML Research

Data Quality With or Without Apache Spark and Its Ecosystem

Serge Smertin, Databricks

Open Source Data and ML Tools

Observability for Data Pipelines With OpenLineage

Julien Le Dem, Datakin

Data Science, Deep Learning and ML

Delight: An Improved Apache Spark UI, Free, and Cross-Platform

Jean-Yves Stephan, Data Mechanics | Julien Dumazert, Data Mechanics

Apache Spark Internals and Best Practices

Brokering Data: Accelerating Data Evaluation with Databricks White Label

Vinoo Ganesh, Veraset | Nick Chmura, Veraset

Data Science, Deep Learning and ML