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Apache: Big Data North America 2017 will be held at the Intercontinental Miami in Miami, Florida. 

Register now for the event taking place May 16-18, 2017. 

Popular Events

 

#1

Keynote: State of the Feather - Sam Ruby, President, Apache Software Foundation

#2

Keynote: Training Our Team in the Apache Way - Alan Gates, Co-founder, Hortonworks

#3

Keynote: Digital Psychometrics and it's Future Effects on Technology - Sandra Matz, Computational Social Scientist

#4

Keynote: Apache CouchDB: A Tale of Community, Cooperation and Code - Adam Kocoloski, Fellow and CTO for the Watson Data Platform, IBM

#5

Onsite Attendee Reception & Technology Showcase, sponsored by Hortonworks

#6

Starting with Apache Spark, Best Practices and Learning from the Field - Felix Cheung, Microsoft

#7

What It Takes to Process a Trillion Events a Day: Case-Studies in Scaling Stream Processing at LinkedIn - Jagadish Venkatraman, LinkedIn

#8

Breakfast

#9

Creating a Recommender System with ElasticSearch & Apache Spark - Alvaro Santos Andres, Ericsson

#10

Coffee Break

#11

Even Faster: When Presto Meets Parquet @ Uber - Zhenxiao Luo, Uber

#12

Continuous Applications with Apache Spark 2.0 - Peyman Mohajerian, Databricks

#13

From Batch to Streaming ET(L) with Apache Apex - Thomas Weise, Atrato,io

#14

Profiling Spark Applications - Jayesh Thakrar, Conversant

#15

The Continuing Story Of Batching To Streaming Analytics At Optimizely - Michael Borsuk, Optimizely

#16

Lunch ( Attendees on Own)

#17

Apache Hivemall: Scalable Machine Learning Library for Apache Hive/Spark/Pig - Makoto Yui, Treasure Data, Inc. & Takeshi Yamamuro, NTT

#18

Coffee Break

#19

Efficient Columnar Storage with Apache Parquet - Ranganathan Balashanmugam, ThoughtWorks

#20

Leveraging Docker for Hadoop Build Automation and Big Data Stack Provisioning - Evans Ye, Yahoo

#21

Spark SQL + Pig-Latin: Combine Query Language and Data Flow Language for Data Science - Jeff Zhang, Hortonworks

#22

Apache​ ​Mahout:​ ​An​ ​Extendable​ ​Machine​ ​Learning​ ​Framework​ ​for​ ​Spark​ ​and​ ​Flink - Trevor Grant, IBM

#23

Registration

#24

eBay Real-time Business Insight with Streaming Engine Built on Apache Kylin - Ken Wang, eBay

#25

Writing Apache Spark Applications Using Apache Bahir - Luciano Resende & Leucir Marin, IBM

#26

Using Apache Beam for Batch, Streaming, and Everything in Between - Dan Halperin, Google

#27

Keynote Panel Discussion: How to Succeed in IoT 2.0 - Abhi Arunachalam, Battery Ventures; Sudip Chakrabarti, Lightspeed Venture Partners; James Pace, Runtime; Roman Shaposhnik, Pivotal

#28

Apache Beam: Integrating the Big Data Ecosystem Up, Down, and Sideways - Davor Bonaci, Google & Jean-Baptiste Onofré, ASF

#29

Routing Trillion Messages Per Day @Twitter - Lohit Vijayarenu & Gary Steelman, Twitter

#30

Breakfast

#31

Concrete Big Data Use Cases Implemented with Apache Beam - Jean-Baptiste Onofré, Apache Software Foundation

#32

TensorFlow in the Wild: From Cucumber Farmer to Global Insurance Firm - Kazunori Sato, Google

#33

Expanding Apache Zeppelin into Your Cluster - Jongyoul Lee, ZEPL

#34

A Practical Approach to Using Graph Databases and Analytics - Greg Jordan, Graph Story

#35

Dataservices: Processing Big Data the Microservice Way - Josef Adersberger, QAware GmbH

#36

Building Streaming Data Pipelines with Stateful Operations - Chandni Singh, Simplifi.it

#37

General Durable Object and Native Computing Model for Apache Big Data Platforms - Johnu George, Cisco

#38

Coffee Break

#39

Actionable Insights with Apache Apex - Devendra Tagare, DataTorrent Inc.

#40

Leveraging the GPU on Spark - Tobias Polzer, QAware GmbH

#41

Lunch ( Attendees on Own)

#42

Coffee Break

#43

Challenges of Monitoring Distributed Systems - Nenad Bozic, SmartCat

#44

Distributed Resource Scheduling Frameworks, Is There a Clear Winner? - Naganarasimha Garla & Varun Saxena, Huawei Technologies

#45

Docker on Hadoop - Daniel Templeton, Cloudera, Inc.

#46

Big Data Analytics Using Apache (Py)Spark For Analyzing IPO Tweets - Dirk Van den Poel, Ghent University

#47

Lessons Learned with Spark & Cassandra - Matthias Niehoff, codecentric AG

#48

Venturing into Large Hadoop Clusters - Varun Saxena & Naganarasimha Garla, Huawei Technologies

#49

Presto - Swiss Army SQL Knife on Hadoop - Marek Gawiński & Dariusz Eliasz, Allegro Group

#50

Secure, UI-Driven Spark/Flink/Kafka-as-a-Service - Jim Dowling, Royal Institute of Technology