Presented By O'Reilly and Cloudera
Make Data Work
September 26–27, 2016: Training
September 27–29, 2016: Tutorials & Conference
New York, NY

Ecommerce conference sessions

Today’s online storefronts are good at procuring transactions but poor in managing customers. Rupert Steffner explains why online retailers must build a complementary intelligence to perceive and reason on customer signals to better manage opportunities and risks along the customer journey. Individually managed customer experience is retailers' next challenge, and fueling AI is the right answer.
Join Max Shron, former consultant on data science and current head of Warby Parker's data science team, for a Q&A all about data science consulting. Bring your questions about getting into the data science consulting business (or your questions about how to transition from consulting to something new). Even if you don't have questions, join in to hear what others are asking.
Narasimhan Sampath and Avinash Ramineni share how Choice Hotels International used Spark Streaming, Kafka, Spark, and Spark SQL to create an advanced analytics platform that enables business users to be self-reliant by accessing the data they need from a variety of sources to generate customer insights and property dashboards and enable data-driven decisions with minimal IT engagement.
Jeff Carpenter describes how data modeling can be a key enabler of microservice architectures for transactional and analytics systems, including service identification, schema design, and event streaming.
Data science has always been a focus at eHarmony, but recently more business units have needed data-driven models. Jonathan Morra introduces Aloha, an open source project that allows the modeling group to quickly deploy type-safe accurate models to production, and explores how eHarmony creates models with Apache Spark and how it uses them.
Clustering algorithms produce vectors of information, which are almost surely difficult to interpret. These are then laboriously translated by data scientists into insights for influencing product and executive decisions. June Andrews offers an overview of a human-in-the-loop method used at Pinterest and LinkedIn that has lead to fast, accurate, and pertinent human-readable insights.
As the world's largest retailer, Walmart relies on data to power the best shopping experience across the Web, mobile, and stores at scale. Every week, more than 240 million people visit a Walmart store or website around the world. Jaya Kolhatkar explains how Walmart is using that transactional data to make shopping more seamless and personalized.
Fifteen years ago, Webvan spectacularly failed to bring grocery delivery online. Speculation has been high that the current wave of on-demand grocery delivery startups will meet similar fates. Jeremy Stanley explains why this time the story will be different—data science is the key.
Daniel Mintz dives into case studies from three companies—ThredUp, Twilio, and Warby Parker—that use data to generate sustainable competitive advantages in their industries.
Zillow pioneered providing access to unprecedented information about the housing market. Long gone are the days when you needed an agent to get comparables and prior sale and listing data. And with more data, data science has enabled more use cases. Jasjeet Thind explains how Zillow uses Spark and machine learning to transform real estate.