Sep 23–26, 2019

Schedule: Sponsored sessions

9:00am - 5:00pm Monday, September 23 & Tuesday, September 24
Location: 1A 04/05
Jeff Davis (Google Cloud)
Jeff Davis provides a hands-on introduction to designing and building machine learning models on structured data on Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, you'll learn machine learning (ML) concepts and how to implement them using both BigQuery Machine Learning and TensorFlow and Keras. Read more.
9:00am5:00pm Tuesday, September 24, 2019
Location: 1A 07
Matt Kirk (YourChiefScientist.com), Miguel Maldonado (IBM)
Note: This free workshop, courtesy of IBM, is open to the first 50 registrants. You'll take a fascinating deep dive into the power and applications of machine learning in the enterprise. Read more.
9:30am9:40am Wednesday, September 25, 2019
Location: 3E
James Malone (Google)
Open source has always been a core pillar of Google Cloud’s data and analytics strategy. James Malone examines how, as the community continues to set industry standards, the company continues to integrate those standards into its services so organizations around the world can unlock the value of data faster. Read more.
10:00am10:05am Wednesday, September 25, 2019
Location: 3E
Jeremy Rader (Intel)
Data analytics is the long-standing but constantly evolving science that companies leverage for insight, innovation, and competitive advantage. Jeremy Rader explores Intel’s end-to-end data pipeline software strategy designed and optimized for a modern and flexible data-centric infrastructure that allows for the easy deployment of unified advanced analytics and AI solutions at scale. Read more.
10:20am10:25am Wednesday, September 25, 2019
Location: 3E
Nikita Shamgunov (MemSQL)
Data is now the world’s most valuable resource, with winners and losers decided every day by how well we collect, analyze, and act on data. However, most companies struggle to unlock the full value of their data, using outdated, outmoded data infrastructure. Nikita Shamgunov examines how businesses use data, the new demands on data infrastructure, and what you should expect from your tools. Read more.
10:25am10:30am Wednesday, September 25, 2019
Location: 3E
Siva Sivakumar (Cisco)
Siva Sivakumar explains the Cisco Data Intelligence Platform (CDIP), which is a cloud-scale architecture that brings together big data, AI and compute farm, and storage tiers to work together as a single entity, while also being able to scale independently to address the IT issues in the modern data center. Read more.
11:20am12:00pm Wednesday, September 25, 2019
Location: 1A 04/05
Praveen Chitrada (Akamai Technologies)
Praveen Chitrada walks you through how Akamai uses MemSQL, Docker, Airflow, Prometheus, and other technologies as an enabler to streamline and accelerate data ingestion and calculation to generate usage metrics for billing, reporting, and analytics at massive scale. Read more.
11:20am12:00pm Wednesday, September 25, 2019
Location: 1A 01/02
James Malone (Google)
James Malone takes a deep dive into how customers across the world partner with Google Cloud to reimagine big data processing and data lakes while generating incredible business value. Read more.
11:20am12:00pm Wednesday, September 25, 2019
Location: 1E 06
Han Yang (Cisco), Karthik Kulkarni (Cisco)
Artificial intelligence and machine learning are well beyond the laboratory exploratory stage of deployment. In fact, the speed of AI and ML deployment has a huge impact on an organization’s financial income. Chiang Yang and Karthik Kulkarni explore how the Cisco Data Intelligence Platform can help bridge the gap between AI and ML and big data. Read more.
11:20am12:00pm Wednesday, September 25, 2019
Location: 1A 03
Jeremy Rader (Intel)
This session will reveal first-hand insights of an Intel analytics practitioner, share Intel IT’s own data maturity journey and provide actionable best known methods (BKMs) for Enterprises amidst transformation into an intelligent data-first business. Read more.
11:20am12:00pm Wednesday, September 25, 2019
Location: 1E 17
Madhu Kochar (IBM)
An economic revolution is underway, driven by advancements in AI and multicloud technologies. Businesses are crafting strategic plans to modernize their data architecture for this emerging reality, and at the top of their wish list is the ability to virtualize all their data regardless of where it lives. Madhu Kochar explores the data advancements on the horizon. Read more.
12:30pm1:10pm Wednesday, September 25, 2019
Location: 3B - Expo Hall
Blake DuBois (Google)
Taking advantage of cloud infrastructure and analytic services is a must for any digital enterprise. Join Google Cloud as they discuss 10 things you should know about running and migrating on-prem Hadoop deployments to GCP. Read more.
1:15pm1:55pm Wednesday, September 25, 2019
Location: 1A 01/02
Diana Shaw (SAS)
Companies today are working to adopt data-driven mind-sets, strategies, and cultures. Yet the ugly truth is many still struggle to make analytics actionable. Diana Shaw outlines a simple, powerful, and automated solution to operationalize all types of analytics at scale. You'll learn how to put analytics into action while providing model governance and data scalability to drive real results. Read more.
1:15pm1:55pm Wednesday, September 25, 2019
Location: 1E 06
Peter Wang (Anaconda)
Peter Wang explores why data science shouldn’t be seen as merely another technical job within the business and why open source is such a critical aspect of innovation in the field of data science. Read more.
1:15pm1:55pm Wednesday, September 25, 2019
Location: 1A 04/05
See-Kit Lam (Malwarebytes), Darren Chinen (Malwarebytes)
Developing, deploying and managing AI and anomaly detection models is tough business. See-Kit Lam details how Malwarebytes has leveraged containerization, scheduling, and orchestration to build a behavioral detection platform and a pipeline to bring models from concept to production. Read more.
1:15pm1:55pm Wednesday, September 25, 2019
Location: 1A 03
John DesJardins (Hazelcast)
In this talk, we will explore the challenges with integrating real-time stream processing and machine learning into banking and capital markets applications. Read more.
1:15pm1:55pm Wednesday, September 25, 2019
Location: 1E 17
Ben Lackey (Oracle)
Learn about running AI/ML solutions like H2O.ai and Kinetica on Oracle Cloud. The session will include a live demo of Terraform, Oracle Cloud Infrastructure, GPUs and Oracle Marketplace. We’ll discuss other leading Data and AI products including Cloudera, DataStax and Confluent. Read more.
2:05pm2:45pm Wednesday, September 25, 2019
Location: 1A 04/05
Aaron Swanson (Talend)
Winning the hearts and minds of millennials and Gen Z is not an easy task. ALDO has devised a data-driven strategy to create the best consumer experience. Today ALDO relies on Talend and AWS. Aaron Swanson explains the choices made for its data architecture and the hurdles the teams had to solve to turn the vision into reality. Read more.
2:05pm2:45pm Wednesday, September 25, 2019
Location: 1A 01/02
Oftentimes there's a fracture between the highly governed data of enterprise IT systems and the comprehensive but often ungoverned world of large-scale data lakes and streams of data from blogs, system logs, sensors, IoT devices, and more. Kevin Poskitt and Andreas Wesselmann walk you through how AI needs to connect to all of this data, as well as image, video, audio, and text data sources. Read more.
2:05pm2:45pm Wednesday, September 25, 2019
Location: 1E 06
Olga Lagunova (Pitney Bowes), John Derrico (Mastercard)
Mastercard and Pitney Bowes have overcome many challenges on their journey to accelerate innovation, achieve efficiencies, and improve the overall customer experience. Olga Lagunova and John Derrico share lessons learned as the data strategy evolved and highlight pitfalls and solutions from data science projects across several industries, from finance to cross-border shipping logistics. Read more.
2:05pm2:45pm Wednesday, September 25, 2019
Location: 1A 03
Amar Arsikere (infoworks.io)
The breakneck pace of business change and its insatiable appetite for data and analytics to drive Digital Transformation makes agile use of data an imperative. Read more.
2:55pm3:35pm Wednesday, September 25, 2019
Location: 1A 04/05
Jungwook SEo (SK Holdings)
Jungwook Seo walks you through a data analytics platform in the cloud by the name of AccuInsight+ with eight data analytic services in the CloudZ (one of the biggest cloud service providers in Korea), which SK Holdings announced in January 2019. Read more.
2:55pm3:35pm Wednesday, September 25, 2019
Location: 1E 06
Digital location data is a crucial part of data science. The "where" matters as much to an analysis as the "what" and the "why." Shannon Kalisky and Alberto Nieto explore tools that help you apply a range of geospatial techniques in your data science workflows to get deeper insights. Read more.
2:55pm3:35pm Wednesday, September 25, 2019
Location: 1A 01/02
Dong Li (Kyligence), Hongbin Ma (Kyligence)
Your analytics are biased. Efforts to extract meaning by manually scrubbing, indexing, and parsing big data is limited by time, cost, and human assumptions. Dong Li and Hongbin Ma offer an overview of augmented analytics. It takes OLAP into the future with AI, ensuring objective and unique insights that cover all relevant scenarios found in petabytes of multidimensional and variable data. Read more.
2:55pm3:35pm Wednesday, September 25, 2019
Location: 1A 03
Radhika Ravirala (Amazon Web Services)
Radhika Ravirala explains how to migrate your workloads to Amazon EMR. Join in to learn the key motivations and benefits from a move to the cloud, along with the architectural changes required and best practices you can use right away. Read more.
2:55pm3:35pm Wednesday, September 25, 2019
Location: 1E 17
Anant Chintamaneni (HPE (BlueData)), Matt Maccaux (HPE (BlueData))
Anant Chintamaneni and Matt Maccaux explore whether the combination of containers with large-scale distributed data analytics and machine learning applications is like combining oil and water— or like peanut butter and chocolate. Read more.
4:35pm5:15pm Wednesday, September 25, 2019
Location: 1A 03
Chuck Yarbrough (Hitachi Vantara)
According to Gartner, over 80% of data lake projects were deemed inefficient. Data lakes come and go. Swamps happen. Data agility is fleeting. Chuck Yarbrough walks you through how data ops practices and a modern data architecture bring greater visibility and allow faster data access with proper governance. Read more.
4:35pm5:15pm Wednesday, September 25, 2019
Location: 1E 17
Daniel D'Orazio (Matillion)
According to Forrester, insight-driven companies are on pace to make $1.8 trillion annually by 2021. Daniel D'Orazio wants to know how fast your team can collect, process, and analyze data to solve present—and future—business challenges. You'll gain actionable tips and lessons learned from cloud data warehouse modernizations at companies like DocuSign that you can take back to your business. Read more.
4:35pm5:15pm Wednesday, September 25, 2019
Location: 1E 06
Barbara Petrocelli (Cambridge Semantics), Peter Ball (Consultant)
Join industry consultant Peter Ball, of Liminal Innovation, and Barbara Petrocelli, VP Field Operations of Cambridge Semantics, to learn how enterprise data fabrics are reshaping the modern data management landscape. Read more.
4:35pm5:15pm Wednesday, September 25, 2019
Location: 1A 01/02
Amit Assudani (Impetus)
Data lakes and analytical processing on the cloud is a reality. This presents new challenges for DevOps, with respect to Governance, Continuous Integration & Deployment, etc. This session will present our views on how to maintain sanity in your development organization while implementing the many dimensions of building an efficient cloud-based data platform and application development environment. Read more.
5:25pm6:05pm Wednesday, September 25, 2019
Location: 1A 04/05
David Leichner (SQream)
What started as an asset for data scientists and BI professionals has become a poorly performing problem. David Leichner explores the Hadoop ecosystem and relational databases from an analytics perspective—reviewing the current landscape, what Hadoop was designed for, and how a Hadoop-based infrastructure can be improved to support a new era of exponentially growing data. Read more.
5:25pm6:05pm Wednesday, September 25, 2019
Location: 1E 17
Ben Sharma (Zaloni), Santanu Sengupta (Nuveen)
Ben Sharma and Santanu Sengupta walk you through how to quickly integrate and accelerate environmental, social, and governance (ESG) data and third-party data into your environment to provide governed, trusted, and traceable data to portfolio managers and analysts in a self-service manner. Read more.
9:15am9:25am Thursday, September 26, 2019
Location: 3E
Daniel Hernandez takes a deep dive into how, with a unified, prescriptive information architecture, organizations can successfully unlock the value of their data for an AI and multicloud world. Read more.
9:35am9:40am Thursday, September 26, 2019
Location: 3E
Barbara Eckman (Comcast)
Barbara Eckman shares lessons learned from early big data mistakes and the progress her team at Comcast is making toward a postrevolutionary big data vision. Read more.
9:40am9:45am Thursday, September 26, 2019
Location: 3E
Edward Jezierski (Microsoft)
Microsoft has an ecosystem spanning research, gaming, and the cloud that's advancing reinforcement learning (RL) and putting it into everyday use. Join Edward Jezierski to see where RL is used practically across Microsoft and imagine the opportunities that exist for your business today. Read more.
10:15am10:20am Thursday, September 26, 2019
Location: 3E
Jed Dougherty (Dataiku)
Jed Dougherty presents the trailer of the upcoming _Data Science Pioneers_ documentary about the passionate data scientists driving us toward technological revolution. Cut through the hype with _Data Science Pioneers_ and see what it really means to be a data scientist. Read more.
11:20am12:00pm Thursday, September 26, 2019
Location: 1A 04/05
Charles Boicey (Clearsense)
Healthcare’s reliance on comprehendible data is critical to the mission of providing optimal and affordable care. Charles Boicey takes a deep dive into how the application of technology, such as machine learning, is paramount to the modernization of healthcare that provides its professionals with fully integrated and complete medical records. Read more.
11:20am12:00pm Thursday, September 26, 2019
Location: 1A 03
Edward Jezierski (Microsoft), Jackie Nichols (Microsoft)
Edward Jezierski and Jackie Nichols demonstrate how Cognitive Services Personalizer works with your content and data, how it autonomously learns to make optimal decisions, how you can add it to your app with two lines of code, and what’s under the hood. Then they share the results Personalizer achieved on the Xbox One home page as well as best practices for applying it in your applications today. Read more.
11:20am12:00pm Thursday, September 26, 2019
Location: 1A 01/02
AI isn't magic. It’s still hard work. Daniel Hernandez explains why having the technology alone isn't enough; it requires a thoughtful and well-architected approach. Read more.
11:20am12:00pm Thursday, September 26, 2019
Location: 1E 06
Ajay Anand (Kyvos Insights)
Learn how you can overcome the challenges of traditional OLAP solutions and scale BI to deliver quick insights to business users across your enterprise Read more.
1:15pm1:55pm Thursday, September 26, 2019
Location: 1E 06
Dan DeMers (Cinchy)
After 40 years of apps, enterprise companies now realize that building or buying an application for every use case has become a major threat to their ability to leverage and protect their core data assets. Dan DeMers provides a live demo of Cinchy, the world’s first data collaboration platform. Read more.
1:15pm1:55pm Thursday, September 26, 2019
Location: 1A 03
Paul Scott-Murphy (WANdisco)
Paul Scott-Murphy dives into the options that exist for cloud migration and their advantages and disadvantages, what cloud vendors do and don't offer to support large-scale migration, the business risks associated with large-scale cloud migration, and how to migrate analytics data at scale for immediate use in Spark without disrupting on-premises operations. Read more.
1:15pm1:55pm Thursday, September 26, 2019
Location: 1A 04/05
Paul Wolmering (Actian Corporation)
Paul Wolmering explores the key characteristics for building an Agile data warehouse and defines a reference architecture for hybrid data. Read more.
1:15pm1:55pm Thursday, September 26, 2019
Location: 1A 01/02
Jed Dougherty (Dataiku)
Jed Dougherty takes a deep dive into an often overlooked aspect of the data science lifecycle: model deployment. Once they’ve constructed a data science model that does a good job accurately predicting their test set, many data scientists think the job is over. But really, it’s just begun. Read more.
2:05pm2:45pm Thursday, September 26, 2019
Location: 1A 01/02
Jim Cushman (Collibra), Piyush Jain (Progressive)
Transforming data into a trusted business asset that informs decision making requires giving teams access to a powerful platform that makes it easy to harness data across the enterprise. Jim Cushman and Piyush Jain detail how Progressive uses Collibra to transform the way data is managed and used across the organization, driving real business value. Read more.
2:05pm2:45pm Thursday, September 26, 2019
Location: 1A 04/05
Matt Derda (Trifacta), Yogesh Prasad (IQVIA)
Clinical trial data analysis can be a complex process. The data is typically hand-coded and formatted differently and is required to be delivered in an FDA-approved format. Matt Derda and Yogesh Prasad explain how IQVIA built its Clean Patient Tracker and how it enabled agility and flexibility for end users of the platform, from data acquisition to reporting and analytics. Read more.

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