Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA

Schedule: Enterprise adoption sessions

How big data finds its way into big organizations: what enterprises are doing to embrace data science, machine learning, and the decision-making power of analytics.

11:00am11:40am Wednesday, March 15, 2017
Location: 230 A Level: Beginner
Secondary topics:  Architecture, Data Platform, Streaming
Felix Gorodishter (GoDaddy)
Average rating: ****.
(4.25, 4 ratings)
GoDaddy ingests and analyzes 100,000 EPS of logs, metrics, and events each day. Felix Gorodishter shares GoDaddy's big data journey and explains how the company makes sense of 10+-TB-per-day growth for operational insights of its cloud leveraging Kafka, Hadoop, Spark, Pig, Hive, Cassandra, and Elasticsearch. Read more.
1:50pm2:30pm Wednesday, March 15, 2017
Location: 230 A Level: Intermediate
Secondary topics:  Architecture, Data Platform
Eric Richardson (American Chemical Society)
Average rating: **...
(2.50, 2 ratings)
Eric Richardson explains how ACS used Hadoop, HBase, Spark, Kafka, and Solr to create a hybrid cloud enterprise data hub that scales without drama and drives adoption by ease of use, covering the architecture, technologies used, the challenges faced and defeated, and problems yet to solve. Read more.
2:40pm3:20pm Wednesday, March 15, 2017
Location: 230 A Level: Intermediate
Secondary topics:  Architecture, Data Platform
Gwen Shapira (Confluent), Bob Lehmann (Bayer)
Average rating: ****.
(4.50, 2 ratings)
Gwen Shapira and Bob Lehmann share their experience and patterns building a cross-data-center streaming data platform for Monsanto. Learn how to facilitate your move to the cloud while "keeping the lights on" for legacy applications. In addition to integrating private and cloud data centers, you'll discover how to establish a solid foundation for a transition from batch to stream processing. Read more.
4:20pm5:00pm Wednesday, March 15, 2017
Location: 230 A Level: Beginner
Ganesh Prabhu (FireEye), Vivek Agate (FireEye), Alex Rivlin (FireEye)
Ganesh Prabhu, Alex Rivlin, and Vivek Agate share an approach that enabled a small team at FireEye to migrate 20 TB of RDBMS data comprised of 250+ tables and nearly 2,000 partitions to Hadoop and an adaptive platform that allows migration of a rapidly changing dataset to Hive. Along the way, they explore some of the challenges typical for a company implementing Hadoop. Read more.
5:10pm5:50pm Wednesday, March 15, 2017
Location: 230 A Level: Intermediate
Marcel Kornacker (Cloudera), Mostafa Mokhtar (Cloudera)
Average rating: ****.
(4.50, 2 ratings)
Marcel Kornacker and Mostafa Mokhtar help simplify the process of making good SQL-on-Hadoop decisions and cover top performance optimizations for Apache Impala (incubating), from schema design and memory optimization to query tuning. Read more.
4:20pm5:00pm Thursday, March 16, 2017
Location: LL20 C Level: Intermediate
Nandu Jayakumar (Oracle), Rajesh Bhargava (Visa)
Average rating: *****
(5.00, 2 ratings)
Visa is transforming the way it manages data: database appliances are giving way to Hadoop and HBase, and proprietary ETL is being replaced by Spark. Nandu Jayakumar and Rajesh Bhargava discuss the adoption of big data practices at this conservative financial enterprise and contrasts it with the adoption of the same ideas at Nandu's previous employer, a web/ad-tech company. Read more.