Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA

Schedule: Data-driven business management sessions

9:00am12:30pm Tuesday, March 14, 2017
Location: LL20 C
Edd Wilder-James (Google), Ellen Friedman (MapR Technologies), Jim Scott (MapR Technologies), GABRIELA QUEIROZ (R-Ladies), Melanie Warrick (Google), Aneesh Karve (Quilt)
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.
9:00am5:00pm Tuesday, March 14, 2017
Location: LL20 B
Michael Abbott (Stanford University), Christopher Pouliot (Nio), Jennifer Anderson, Renee DiResta (New Knowledge), Coco Krumme (Haven | UC Berkeley), Ryan Baumann (Mapbox), JAVONA WHITE BEAR (IBM), Andre Luckow (BMW Group), Rajiv Paul (Yakit), Evangelos Simoudis (Synapse Partners), Roland Major (Transport for London), Rodrigo Fontecilla (Unisys), Lloyd Palum (Vnomics), Andreas Ribbrock (#zeroG, A Lufthansa Systems Company)
Data, Transportation, and Logistics Day offers a daylong deep-dive into how data science is changing transportation and logistics. We’ll investigate the latest advances in and applications of self-driving vehicles, automated drones, and embedded sensors and explore how new uses of data are challenging the industry to evolve infrastructure for the future. Read more.
1:30pm5:00pm Tuesday, March 14, 2017
Location: LL20 C
William Schmarzo (Dell EMC)
Average rating: *****
(5.00, 4 ratings)
Organizations need a model to measure how effectively they are using data and analytics. Once they know where they are and where they need to go, they then need a framework to determine the economic value of their data. William Schmarzo explores techniques for getting business users to “think like a data scientist” so they can assist in identifying data that makes the best performance predictors. Read more.
1:30pm5:00pm Tuesday, March 14, 2017
Location: 210 B/F Level: Intermediate
Edd Wilder-James (Google), Scott Kurth (Silicon Valley Data Science)
Average rating: ****.
(4.17, 6 ratings)
Big data and data science have great potential for accelerating business, but how do you reconcile the business opportunity with the sea of possible technologies? Data should serve the strategic imperatives of a business—those aspirations that will define an organization’s future vision. Scott Kurth and Edd Wilder-James explain how to create a modern data strategy that powers data-driven business. Read more.
11:00am11:40am Wednesday, March 15, 2017
Location: 210 D/H Level: Intermediate
Jack Norris (MapR Technologies)
Average rating: ****.
(4.33, 3 ratings)
Leading companies are integrating operations and analytics to make real-time adjustments to improve revenues, reduce costs, and mitigate risks. There are many aspects to digital transformation, but the timely delivery of actionable data is both a key enabler and an obstacle. Jack Norris explores how companies from TransUnion to Uber use event-driven processing to transform their businesses. Read more.
11:50am12:30pm Wednesday, March 15, 2017
Location: 210 D/H Level: Non-technical
Yael Garten (LinkedIn)
Average rating: ****.
(4.91, 11 ratings)
Data science is a rewarding career. It's also really hard—not just the technical work itself but also "how to do the work well" in an organization. Yael Garten explores what data scientists do, how they fit into the broader company organization, and how they can excel at their trade and shares the hard and soft skills required, tips and tricks for success, and challenges to watch out for. Read more.
11:00am11:40am Thursday, March 16, 2017
Location: 210 C/G Level: Non-technical
Mehmet Irmak Sirer (Datascope Analytics)
Average rating: ***..
(3.83, 12 ratings)
In a data-driven organization, vice presidents, directors, and managers play a crucial role as translators between senior leadership and data science teams. They don’t need to be full-fledged data scientists, but they do need data science "street smarts” in order to succeed in this critical task. Mehmet Irmak Sirer outlines the skills they need and gives practical ways to improve them. Read more.
1:50pm2:30pm Thursday, March 16, 2017
Location: 210 C/G Level: Non-technical
Secondary topics:  Data for good
Gillian Docherty (The Data Lab)
Average rating: ****.
(4.33, 3 ratings)
Gillian Docherty shares her experience leading The Data Lab, an innovation center focused on helping organizations drive economic and social benefit through data science and analytics. Along the way, Gillian discusses some of the projects her teams have supported, from multinationals to startups, and explains how they leverage academic capability to help drive innovation from data. Read more.
2:40pm3:20pm Thursday, March 16, 2017
Location: 210 C/G Level: Intermediate
Secondary topics:  ecommerce, Retail
Eric Colson (Stitch Fix)
Average rating: ****.
(4.36, 14 ratings)
Data scientists blend the skills of statisticians, software engineers, and domain experts to create new roles. Data science isn't merely an amalgam of disciplines but rather a gestalt which synthesizes the ethos of various fields. This merits new thinking when it comes to organization. Eric Colson explores some novel—and often unintuitive—ways to unleash the value of your data science team. Read more.
2:40pm3:20pm Thursday, March 16, 2017
Location: LL21 A Level: Intermediate
Christopher Bergh (DataKitchen), Gil Benghiat (DataKitchen)
Average rating: ****.
(4.50, 2 ratings)
Data analysts, data scientists, and data engineers are already working on teams delivering insight and analysis, but how do you get the team to support experimentation and insight delivery without ending up in an IT versus data engineer versus data scientist war? Christopher Bergh and Gil Benghiat present the seven shocking steps to get these groups of people working together. Read more.
4:20pm5:00pm Thursday, March 16, 2017
Location: 210 C/G Level: Non-technical
Robert Cohen (Economic Strategy Institute)
Programmable enterprises are developing their businesses around cloud computing, big data, and the internet of things. Robert Cohen explores how infrastructure changes will alter corporate use of software, skilled employees, and strategies, the business and economic impacts of these changes, and the broader impacts of these shifts on our economy and society. Read more.