Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

Schedule: Enterprise adoption sessions

9:00am12:30pm Tuesday, September 26, 2017
Location: 1E 11
Dan Roesch (Roesch & Associates LLC), Dan Roesch (Roesch & Associates LLC), Edd Wilder-James (Google), Mikio Braun (Zalando), Javier Esplugas (DHL Supply Chain), Kevin Parent (Conduce), Jim Scott (NVIDIA), Melanie Warrick (Google), Sarah Manning (Etsy)
Data 101 introduces you to core principles of data architecture, teaches you how to build and manage successful data teams, and inspires you to do more with your data through real-world applications. Setting the foundation for deeper dives on the following days of Strata + Hadoop World, Data 101 reinforces data fundamentals and helps you focus on how data can solve your business problems. Read more.
11:20am12:00pm Wednesday, September 27, 2017
Location: 1A 18 Level: Intermediate
Secondary topics:  Financial services
Atul Dalmia (American Express)
Big data decisioning is critical to driving real-time business decisions in our digital age. But how do you begin the transformation to big data? The key is enterprise adoption across a variety of end users. Atul Dalmia shares best practices learned from American Express's five-year journey, the biggest challenges you’ll face, and ideas on how to solve them. Read more.
1:15pm1:55pm Wednesday, September 27, 2017
Location: 1A 18 Level: Advanced
Milind Nagnur (Citigroup)
Average rating: **...
(2.00, 2 ratings)
Milind Nagnur explores the requirements for a next-generation platform for data management, covering everything from controlled exploratory sandboxes to hosting transactional applications, and explains how modern, industry-leading data management tools and self-service analytics can address these needs. Read more.
2:05pm2:45pm Wednesday, September 27, 2017
Location: 1A 18 Level: Intermediate
Secondary topics:  Financial services, Platform
Average rating: *....
(1.00, 1 rating)
At Visa, the process of optimizing the enterprise data warehouse and consolidating data marts by migrating these analytic workloads to Hadoop has played a key role in the adoption of the platform and how data has transformed Visa as an organization. Nandu Jayakumar and Justin Erickson share Visa’s journey along with some best practices for organizations migrating workloads to Hadoop. Read more.
2:55pm3:35pm Wednesday, September 27, 2017
Location: 1A 23/24 Level: Beginner
Secondary topics:  Platform, Sales
Simon Chan (Salesforce)
Average rating: *****
(5.00, 1 rating)
Salesforce recently released Einstein, which brings AI into its core platform to power every business. The secret behind Einstein is an underlying platform that accelerates AI development at scale for both internal and external data scientists. Simon Chan shares his experience building this unified platform for a multitenancy, multibusiness cloud enterprise. Read more.
2:55pm3:35pm Wednesday, September 27, 2017
Location: 1E 10/11 Level: Beginner
Secondary topics:  AI, Marketing
Elsie Kenyon (Nara Logics)
Average rating: **...
(2.67, 3 ratings)
Enterprises today pursue AI applications to replace logic-based expert systems in order to learn from customer and operational signals. But training data is often limited or nonexistent, and applying or extrapolating the wrong dataset can be costly to a company's business and reputation. Elsie Kenyon explains how to harness institutional human knowledge to augment data in deployed AI solutions. Read more.
5:25pm6:05pm Wednesday, September 27, 2017
Location: 1A 18 Level: Advanced
Jerrard Gaertner (Ryerson University)
Average rating: *****
(5.00, 1 rating)
Engaging, teaching, mentoring, and advising mature, mostly employed, often enthusiastic and ambitious adult learners at University of Toronto has taught Jerrard Gaertner more about analytics in the real world than he ever imagined. Jerrard shares stories he learned about everything from hyped-up expectations and internal sabotage to organizational streamlining and creating transformative insight. Read more.
4:35pm5:15pm Thursday, September 28, 2017
Location: 1A 23/24 Level: Non-technical
Bob Eilbacher (Caserta)
Building an efficient analytics environment requires a strong infrastructure. Bob Eilbacher explains how to implement a strong DevOps practice for data analysis, starting with the necessary cultural changes that must be made at the executive level and ending with an overview of potential DevOps toolchains. Read more.