Loading…
Apache: Big Data 2016 has ended
Register Now or Visit the Website for more Information 
DD

Darryl Dutton

T4G
Halifax, N.S.
Monday, May 9
 

10:40am PDT

The Evolution of Apache Kylin: Realtime and Plugin Architecture in Kylin2 - Luke Han, Apache Kylin Regency E

11:40am PDT

SAMOA: A Platform for Mining Big Data Streams - Nicolas Kourtellis, Telefonica Plaza A

2:00pm PDT

Data Science Applied: A Utilities Sector Case Study - Bram Steurtewagen Regency E Will It Scale? The Secrets Behind Scaling Stream-processing Applications - Navina Ramesh, LinkedIn Plaza A

3:00pm PDT

Druid: Interactive Exploratory Analytics at Scale - Fangjin Yang, Imply Georgia A Introduction to Apache Kudu (Incubating) for Timeseries Storage - Dan Burkert, Cloudera Regency E

4:10pm PDT

Delivering Realtime and Agile Analytics Using Apache Kafka, Spark & Drill - Neeraja Rentachintala, MapR technologies Plaza C Next Gen Big Data Analytics with Apache Apex - Thomas Weise, DataTorrent Georgia A Everyone Plays: Collaborative Data Science with Zeppelin - Trevor Grant, Market6 Regency E

5:10pm PDT

Next-Gen Decision Making in Under 2ms - Ilya Ganelin, Capital One Data Innovation Lab Plaza B The New Time Series Kid on the Block - Florian Lautenschlager, QAware GmbH Regency E
 
Tuesday, May 10
 

9:00am PDT

Random Forest Clustering with Apache Spark - Erik Erlandson, Red Hat, Inc. Plaza C

10:00am PDT

Breaking Spark: Top 5 Mistakes to Avoid When Using Apache Spark in Production - Neelesh Srinivas Salian, Cloudera Georgia B Clickstream Analysis with Apache Spark - Andreas Zitzelsberger, QAware GmbH Plaza C

11:20am PDT

Streaming Data Integration at Scale with Kafka - Ewen Cheslack-Postava, Confluent Regency A A Java Implementer’s Guide to Boosting Apache Spark Performance - Tim Ellison, IBM Georgia B Get the Best Out of Hive and Spark - Xuefu Zhang, Uber Georgia A

2:00pm PDT

Building a Self-serve Kafka Ecosystem - Joel Koshy, LinkedIn Regency A On the Fly Retraining of Predictive Analytical Models Using Spark Streaming: An Equity-price Direction Prediction Case Study - Tijl Carpels, Ghent University Plaza C

3:00pm PDT

From Big Data to Mobile Data with Apache CouchDB and PouchDB - Bradley Holt, IBM Cloudant Plaza B Real Time BOM Explosions with Apache Solr and Spark - Andreas Zitzelsberger, QAware GmbH Plaza C Using Kafka and Kudu for Fast, Low-latency SQL Analytics on Streaming Data - Mike Percy & Ashish Singh, Cloudera Georgia A
 
Wednesday, May 11
 

10:50am PDT

Spark After Dark 2.0: Complete End-to-End, Real-time Advanced Analytics, Big Data Reference Pipeline Including Machine Learning, Graph Processing, and Text/NLP Analytics, and Streaming Approximations Using Kafka... Plaza C

11:50am PDT

Apache Zeppelin and It’s Pluggable Architecture for Your Data Science Environment - Moon Soo Lee, NFLabs Regency A

2:00pm PDT

Combining Machine Learning Frameworks with Apache Spark - Tim Hunter, Databricks, Inc. Georgia A

3:00pm PDT

Crowd Learning for Indoor Positioning - Thomas Burgess, indoo.rs GmbH Plaza A Real-world Analytics with Solr Cloud and Spark - Johannes Weigend, QAware GmbH Georgia A

4:10pm PDT

Data Science for the Datacenter: Analyzing Logs with Apache Spark - William Benton, Red Hat, Inc Plaza B

5:10pm PDT

Mining Public Datasets Using Apache Zeppelin (incubating) and Spark - Alexander Bezzubov, NFLabs Plaza C