Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Schedule: Sponsored sessions

11:00am–11:40am Wednesday, March 7, 2018
Digital transformation demands faster, more productive data science (sponsored by DataScience.com)
Location: LL20 B
Ian Swanson (DataScience.com)
Average rating: ****.
(4.50, 2 ratings)
Ian Swanson shares strategies for leading more productive data science teams, along with steps you can take today to meet growing demands for AI and machine learning use cases. Read more.
11:00am–11:40am Wednesday, March 7, 2018
Architecting an edge-to-cloud data pipeline to unify multiple data sources and processing engines (sponsored by NetApp)
Location: LL21 A
Santosh Rao (NetApp)
Average rating: *****
(5.00, 1 rating)
Santosh Rao explores the architecture of a data pipeline from edge to core to cloud and across various data sources and processing engines and explains how to build a solution architecture that enables businesses to maximize the competitive differentiation with the ability to unify data insights in compelling yet efficient ways. Read more.
11:00am–11:40am Wednesday, March 7, 2018
Focus on your business: Case studies on building data solutions that meet your needs (sponsored by Microsoft)
Location: 230 B
Tobias Ternstrom (Microsoft)
Average rating: ****.
(4.00, 1 rating)
Tobias Ternstrom leads a deep dive into case studies from three Microsoft customers who put technology before solutions. Tobias examines the decisions that brought them there and outlines how they got back on track and solved their business problems. Read more.
11:50am–12:30pm Wednesday, March 7, 2018
Journey to digital (sponsored by IBM)
Location: LL21 A
Seth Dobrin, PhD (IBM)
Average rating: ***..
(3.00, 1 rating)
Companies that want to become truly digital must take a journey of three steps: data transformation, data science transformation, and digital transformation. This also requires transforming the business with machine learning to fundamentally change the relationship with customers. Seth Dobrin explains the detailed steps along the way to digital transformation—and the pitfalls. Read more.
11:50am–12:30pm Wednesday, March 7, 2018
Analytics in real time, the (Grey's) anatomy of event streaming (sponsored by MemSQL)
Location: 230 B
Adam Ahringer (Disney-ABC TV Digital Media)
Average rating: ***..
(3.20, 5 ratings)
Adam Ahringer explains how Disney-ABC TV leverages Amazon Kinesis and MemSQL to provide real-time insights based on user telemetry as well as the platform for traditional data warehousing activities. Read more.
11:50am–12:30pm Wednesday, March 7, 2018
The four elements of modern analytics (sponsored by MicroStrategy)
Location: LL20 B
Vijay Kotu (Oath)
Average rating: ****.
(4.67, 3 ratings)
Vijay Kotu details how Oath is using MicroStrategy to combine elements of data science, enterprise mobility, information design, and data lakes in its transformation into an intelligent enterprise. Read more.
11:50am–12:30pm Wednesday, March 7, 2018
Speed up mission-critical analytics in the cloud (sponsored by Kyligence)
Location: 210 B/F
Billy Liu (Kyligence)
As organizations look to scale their analytics capability, the need to grow beyond a traditional data warehouse becomes critical, and cloud-based solutions allow more flexibility while being more cost efficient. Billy Liu offers an overview of Kyligence Cloud, a managed Apache Kylin online service designed to speed up mission-critical analytics at web scale for big data. Read more.
1:50pm–2:30pm Wednesday, March 7, 2018
Accelerating analytics and AI from the edge to the cloud (sponsored by Intel)
Location: 230 B
Kevin Huiskes (Intel), Radhika Rangarajan (Intel)
Advanced analytics and AI workloads require a scalable and optimized architecture, from hardware and storage to software and applications. Kevin Huiskes and Radhika Rangarajan share best practices for accelerating analytics and AI and explain how businesses globally are leveraging Intel’s technology portfolio, along with optimized frameworks and libraries, to build AI workloads at scale. Read more.
1:50pm–2:30pm Wednesday, March 7, 2018
Data at scale and speed: Real-world use cases (sponsored by MapR)
Location: LL20 B
Tags: mapr_session
Ted Dunning (MapR, now part of HPE)
Average rating: ****.
(4.67, 3 ratings)
Getting value from data at large scale and on a variety of time scales is hard. True, it's not as hard as it used to be, but you still don’t win by default. Ted Dunning explains why it takes good design, the right technology, and a pragmatic approach to succeed. Read more.
2:40pm–3:20pm Wednesday, March 7, 2018
Managing the intelligent data pipeline and the connected enterprise (sponsored by Hitachi Vantara)
Location: LL21 A
Chuck Yarbrough (Hitachi Vantara)
Intelligently managing the data pipeline is the key to driving business acceleration and reducing costs. Chuck Yarbrough outlines ways to gain control over the data pipeline. Along the way, you’ll learn how cloud, big data, and machine learning models intersect and how streaming and cloud integration can help create the connected enterprise. Read more.
2:40pm–3:20pm Wednesday, March 7, 2018
The Snowflake data warehouse: How Sharethrough analyzes petabytes of event data in a SQL database (sponsored by Snowflake)
Location: 230 B
Dave Abercrombie (Sharethrough)
Average rating: ***..
(3.50, 2 ratings)
Dave Abercrombie explains how Sharethrough used Snowflake to build an analytic and reporting platform that handles petabyte-scale data with ease. Read more.
2:40pm–3:20pm Wednesday, March 7, 2018
Building machine learning systems for scale: Amazon insights and best practices (sponsored by Amazon Web Services)
Location: LL20 B
Guy Ernest (Amazon Web Services)
Average rating: ****.
(4.50, 4 ratings)
Amazon SageMaker is platform to build, train, and deploy machine learning models at any scale. Guy Ernest explores the scalable algorithms that SageMaker provides, distributed training with Apache MXNet and TensorFlow, automatic tuning of hyperparameters, and model deployments. Read more.
4:20pm–5:00pm Wednesday, March 7, 2018
BI and big data convergence in modern cloud architecture (sponsored by Arcadia Data)
Location: LL20 B
terry mcfadden (P&G)
Procter & Gamble relies heavily on data, particularly for BI. Running compute where the data lives is critical for performance, and the company has found added benefits to this architecture, which complements its Hadoop and BI needs. Terry McFadden offers an overview of P&G's modern analytics architecture and explains how it differs from traditional approaches. Read more.
4:20pm–5:00pm Wednesday, March 7, 2018
Winning the big data war pays big dividends for Wargaming (sponsored by SAS)
Location: 230 B
Alexander Ryabov (Wargaming), Jonathan Crow (Wargaming)
Alexander Ryabov and Jonathan Crow explain how Wargaming is winning the battle for bigger profits in the virtual world of online gaming using a best-in-class business intelligence solution to equip its business units with decision-making tools. Read more.
5:10pm–5:50pm Wednesday, March 7, 2018
Bringing AI into the IoT (sponsored by SAS)
Location: 230 B
Evan Guarnaccia (SAS)
Average rating: ***..
(3.00, 1 rating)
As the internet of things grows, there is an increasing need for sophisticated but lightweight analytics at the edge. Evan Guarnaccia walks you through a multiphase analytics approach to IoT data, analyzing data at rest to discover patterns of interest and develop analytical models that can be easily deployed into a streaming analytics engine out at the edge, in the fog, or in the cloud. Read more.
11:00am–11:40am Thursday, March 8, 2018
Building the bridge from big data to machine learning and artificial intelligence (sponsored by Google Cloud)
Location: 230 B
Ryan Lippert (Google Cloud)
Average rating: *****
(5.00, 2 ratings)
If your company isn't good at analytics, it's not ready for AI. Ryan Lippert explains how the right data strategy can set you up for success in machine learning and artificial intelligence—the new ground for gaining competitive edge and creating business value. Read more.
11:00am–11:40am Thursday, March 8, 2018
The changing role of the CDO: Three keys for success (sponsored by MapR)
Location: LL21 A
Tags: mapr_session
Jim Scott (NVIDIA)
Average rating: **...
(2.00, 1 rating)
The value of data is not strictly a function of its size but rather is in the value that can be extracted from it. Jim Scott explains how to identify the right data to leverage to monitor the pulse of fast changing business environments, the best way to integrate analytics into your business processes, and the importance of cross-application data flows. Read more.
1:50pm–2:30pm Thursday, March 8, 2018
Harnessing the cloud to enable connected systems and self-service and accelerate business growth (sponsored by Talend)
Location: LL21 A
Jeff Smits (RingCentral)
Jeff Smits explains how RingCentral is utilizing the cloud, data integration, self-service, and APIs to harvest the immense potential of connected systems. Read more.
2:40pm–3:20pm Thursday, March 8, 2018
On-device deep learning: Trends, technologies, and challenges (sponsored by TalkingData)
Location: 230 B
Andreas Pfadler (TalkingData)
Andreas Pfadler offers an overview of current technological trends for on-device deep learning and edge computing. Along the way, Andreas explores major players and platforms and computational challenges and solutions. Andreas concludes with a discussion of TalkingData's vision for the future of mobile deep learning. Read more.
2:40pm–3:20pm Thursday, March 8, 2018
Get a farm-to-table view of your data: Track data lineage from source to analytics (sponsored by Syncsort)
Location: LL21 A
Tendu Yogurtcu (Syncsort)
Average rating: *....
(1.00, 1 rating)
Chefs must be able to trust the authenticity, quality, and origin of their ingredients; data analysts must be able to do the same of their data—and what happens to it along the way. Tendü Yoğurtçu explains how to seamlessly track the lineage and quality of your data—on and off the cluster, on-premises or in the cloud—to deliver meaningful insights and meet regulatory compliance requirements. Read more.
2:40pm–3:20pm Thursday, March 8, 2018
When tests cry wolf (sponsored by Pure Storage)
Location: LL20 B
Ivan Jibaja (Pure Storage)
Pure Storage redefined QA testing. Using open source technologies like Spark and Kafka, the company deployed a streaming big data analytics pipeline that processes over 70 billion events per day to prioritize, classify, deduplicate, and understand test failures. Ivan Jibaja discusses use cases for big data analytics technologies, the underlying elastic infrastructure, and lessons learned. Read more.