Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA

Financial services conference sessions

2:40pm–3:20pm Wednesday, 03/30/2016
Vishal Bamba (Transamerica), Nitin Prabhu (Transamerica), Jeremy Beck, Amy Wang (
Transamerica built a product recommendation system that can be leveraged across multiple distribution channels to recommend products, serve customer needs, and reduce complexity. Vishal Bamba, Nitin Prabhu, Jeremy Beck, and Amy Wang highlight the machine-learning technology, models, and architecture behind Transamerica's product recommendation platform.
2:40pm–3:20pm Wednesday, 03/30/2016
Sandy Ryza (Clover Health)
Want to build models over data every second from millions of sensors? Dig into the histories of millions of financial instruments? Sandy Ryza discusses the unique challenges of time series data and explains how to work with it at scale. Sandy then introduces the open source Spark-Timeseries library, which provides a natural way of munging, manipulating, and modeling time series data.
5:10pm–5:50pm Wednesday, 03/30/2016
Steven Totman (Cloudera), Nick Curcuru (Mastercard), Robert Bagley (ClickFox), LORI BIEDA (Bank of Montreal)
In a panel discussion, Cloudera's Steve Totman talks about the practicalities and realities of big data-based customer 360 with big data experts Lori Bieda, Nick Curcuru, and Robert Bagley. Attend if you have challenges implementing big data-based customer 360 or just want to learn from the panel's real-world experiences.
4:20pm–5:00pm Thursday, 03/31/2016
Bill Loconzolo (Intuit)
Data initiatives are often approached with a feast-or-famine mentality: go big and do it all or go home. Bill Loconzolo explains how established enterprises can build scalable, secure data pipelines that create connections between central data and product teams and enable business results that matter. Learn the framework Bill developed to realize your big data vision.
12:05pm–12:30pm Tuesday, 03/29/2016
Julia Rodriguez (Eagle Investment Systems)
Designing data visualizations presents unique and interesting challenges: how to tell a compelling story, how to deliver important information in a forthright, clear format, and how to make visualizations beautiful and engaging. Julie Rodriguez shares a few disruptive designs and connects them back to Vizipedia, her compiled data visualization library.
1:50pm–2:30pm Wednesday, 03/30/2016
Nick Turner (Markerstudy)
Nick Turner offers a case study of Markerstudy, an insurance and insurance-related-services company based in the UK that recreated their data platform around Hadoop. Dubbed the Big Data Insight project, the new platform features near real-time reporting and self-service exploration and has resulted in reduced claims costs, better fraud detection, and increased customer-retention rates.
4:20pm–5:00pm Wednesday, 03/30/2016
Mok Choe (TD Bank Group ), Paul Barth (Podium Data)
Learn how TD Bank is creating the bank of the future through IT 3.0. Central to this is business agility, fueled by secure, self-service access to enterprise and market data. Mok Choe and Paul Barth detail the fundamentals for success in this transformation, which started with rapid consolidation of hundreds of data sources onto a Hadoop enterprise data provisioning platform.
11:50am–12:30pm Thursday, 03/31/2016
Jeffrey Shmain (Cloudera), Mohammad Quraishi (Cigna)
How do you implement Apache Hadoop in a large healthcare company with a mature data-analysis infrastructure? Jeffrey Shmain and Mohammad Quraishi describe Cigna's journey toward big data and Hadoop, including an overview of new Hadoop capabilities like heterogeneous data integration and large-scale machine learning.
10:00am–10:30am Tuesday, 03/29/2016
James Crawford (Orbital Insight)
Big data is exploding in space. Constellations of satellites are being launched to monitor the world in all wavelengths—tracking everything from ships to corn harvests. James Crawford explains how machine vision lets us see vast areas at once, while machine learning lets us analyze these images trillions of pixels at a time to recognize patterns that can help with world-changing projects
11:50am–12:30pm Wednesday, 03/30/2016
If you consider user click paths a process, you can apply process mining. Process mining models users based on their actual behavior, which allows us to compare new clicks with modeled behavior and report any inconsistencies. Bolke de Bruin and Hylke Hendriksen explain how ING implemented process mining on Spark Streaming, enabling real-time fraud detection.
5:10pm–5:50pm Wednesday, 03/30/2016
Sudipto Dasgupta (Infosys Limited), Ganesan Pandurangan (Infosys Limited)
Sudipto Dasgupta and Ganesan Pandurangan offer a case study of a large multinational imaging and electronics company that migrated accounts receivable reports to the Hadoop-based open source Infosys Information Platform, which implemented dynamic age bucketing capabilities and reduced the number of end-user views from over 400 to 50.
1:50pm–2:30pm Thursday, 03/31/2016
Scott Donaldson (FINRA), Matt Cardillo (FINRA)
Scott Donaldson and Matt Cardillo detail the security measures and system architecture needed to bring alive a multipetabyte data warehouse via interactive analytics and directed graphs from several trillions of market events, using HBase, EMR, Hive, Redshift, and S3 technologies in a cost-efficient manner.
4:20pm–5:00pm Wednesday, 03/30/2016
John Omernik (MapR Technologies)
John Omernik walks attendees through Operation Ababil's 2013 DDoS attacks to understand how banks were able to implement controls to protect their networks. Using subject-matter experts, Hadoop, and low-friction access to data, members of the US banking industry were able to come up with new models to protect their networks from distributed denial of service attacks.
1:50pm–2:30pm Thursday, 03/31/2016
Ilya Ganelin (Capital One Data Innovation Lab)
What if we have reached the point where open source can handle massively difficult streaming problems with enterprise-grade durability? Ilya Ganelin presents Capital One’s novel solution for real-time decisioning on Apache Apex. Ilya shows how Apex provides unique capabilities that ensure less than 2 ms latency in an enterprise-grade solution on Hadoop.
1:50pm–2:30pm Wednesday, 03/30/2016
Michael Dauber (Amplify Partners), Shivon Zilis (Bloomberg Beta), Cack Wilhelm (Scale Venture Partners), Roseanne Wincek (Institutional Venture Partners), Kristina Bergman (Ignition Partners)
In a panel discussion, top-tier VCs look over the horizon and consider the big trends in big data, explaining what they think the field will look like a few years (or more) down the road. Join us as Shivon Zilis, Cack Wilhelm, Michael Dauber, Kristina Bergman, and Roseanne Wincek talk about trends that everyone is seeing and areas for investment that they find exciting.
5:10pm–5:50pm Wednesday, 03/30/2016
Benedikt Koehler (DataLion)
Benedikt Koehler offers approaches to analyzing and visualizing bitcoin data—accessing and downloading the blockchain, transforming the data into a networked data format, identifying hubs and clusters, and visualizing the results as dynamic network graphs—so that typical patterns and anomalies can quickly be identified.