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

September 26-28, 2017
New York, NY

Hilary Mason, Fast Forward Labs

The missing MBA for data-driven business.

Tailored for executives, business leaders, and strategists, you'll learn how some of the world's leading companies build modern data strategies. Discover game-changing technologies and their business applications—and concrete methodologies to move your company forward.

You'll also have access to a hand-picked lineup of Executive Briefings on key issues such as: artificial intelligence; predictive analytics and machine learning; cloud strategy; governance, security, and privacy; bot strategy and automation; and the Internet of Things. View the schedule.

Make data work for business

  • From banking to biotech, retail to government, entertainment to energy—every sector is changing in the face of abundant data. Executives need to make data serve the strategic imperatives of their business.
  • At Strata Business Summit, get the intel you need to build data strategies that drive efficiency and innovation in your business.

Keynote Speakers

Tim O'Reilly

Tim O'Reilly

Founder and CEO, O'Reilly Media, Inc.

WTF? What's the future and why it's up to us

danah boyd

danah boyd

Founder, Microsoft Research | Data & Society

Cathy O'Neil

Cathy O'Neil

Author

Weapons of math destruction

Joanna Bryson

Joanna Bryson

Professor | Affiliate, University of Bath | Princeton Center for IT Policy

The real project of AI ethics

Tanvi Singh

Tanvi Singh

Chief Analytics Officer, CCRO, Credit Suisse

All Strata Data Conference Gold and Silver passes have access to Strata Business Summit Tuesday-Thursday. Platinum and Bronze passes have access to Strata Business Summit Wednesday-Thursday.

Tuesday September 26: Tutorials (Gold & Silver passes)
Location: 1E 06 Location: 1E 07/08 Location: 1E 09
12:30pm | Location: TBD
Lunch
5:00pm | Location: Expo Hall
Opening Reception
Wednesday September 27: Keynotes & Sessions (Gold, Silver & Bronze passes)
Location: 1A 18 Location: 1E 10/11 Location: 1E 12/13
8:45 | Location: 3E
Strata Data Conference Keynotes
12:00pm
Lunch
6:05pm | Location: Expo Hall
Booth Crawl
7:30pm | Location: 230 Fifth Penthouse
Data After Dark
Thursday September 28: Keynotes & Sessions (Gold, Silver & Bronze passes)
Location: 1A 18 Location: 1E 10/11 Location: 1E 12/13
8:45 | Location: 3E
Strata Data Conference Keynotes
12:00pm
Lunch

Register now

Add to your personal schedule
9:00am12:30pm Tuesday, September 26, 2017
Location: 1E 06
Shannon Cutt (O'Reilly Media), Edd Wilder-James (Silicon Valley Data Science), Jim Scott (MapR Technologies), Julie Rodriguez (Eagle Investment Systems), Melanie Warrick (Google)
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.
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9:00am5:00pm Tuesday, September 26, 2017
Location: 1E 09
Rose Winterton (Pitney Bowes), Audrey Spencer-Alvarado (Portland Trail Blazers), Amie Elcan (CenturyLink), Sean Power (Repable), Parisa Foster (Play The Future), Nick Selby (CJX, Inc. | Midlothian Police Department), Salema Rice (Allegis Group)
In a series of 12 half-hour talks aimed at a business audience, you’ll hear data-themed case studies from household brands and global companies, explaining the challenges they wanted to tackle, the approaches they took, and the benefits—and drawbacks—of their solutions. If you want practical insights about applied data, look no further. Read more.
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9:00am5:00pm Tuesday, September 26, 2017
Location: 1E 07/08
Bradford Cross (DCVC), Jason Morton (Ascendant), Leigh Drogen (Estimize), Jessica Stauth (Quantopian), Abraham Thomas (Quandl), Alistair Croll (Solve For Interesting), Robert Passarella (Protege Partners), Vincent-Charles Hodder (www.locallogic.co), Sastry Durvasula (American Express), Priya Koul (American Express), Tanvi Singh (Credit Suisse), José Ribau (CIBC)
Finance is information. From analyzing risk and detecting fraud to predicting payments and improving customer experience, data technologies are transforming the financial industry. And we're diving deep into this change with a new day of data-meets-finance talks, tailored for Strata Data Conference events in the world's financial hubs. Read more.
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1:30pm5:00pm Tuesday, September 26, 2017
Location: 1E 06 Level: Intermediate
John Akred (Silicon Valley Data Science), Heather Nelson (Silicon Valley Data Science)
John Akred and Heather Nelson share methods and observations from three years of effectively deploying data science in enterprise organizations. You'll learn how to build, run, and get the most value from data science teams and how to work with and plan for the needs of the business. Read more.
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10:20am10:35am Wednesday, September 27, 2017
Location: 3E
Cathy O'Neil (Weapons of Math Destruction)
Cathy O'Neil exposes the mathematical models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health. Read more.
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11:20am12:00pm Wednesday, September 27, 2017
Location: 1E 12/13
Michael Chui (McKinsey Global Institute)
Executive Briefing from Michael Chui Read more.
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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.
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11:20am12:00pm Wednesday, September 27, 2017
Location: 1E 10/11 Level: Non-technical
Secondary topics:  Media
Yael Garten (LinkedIn)
Data science is a rewarding career. It's also hard. 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, challenges to watch out for, and tips and tricks for success and #DataScienceHappiness. Read more.
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1:15pm1:55pm Wednesday, September 27, 2017
Location: 1E 10/11
Chris Neumann (500 Startups), Carla Holtze (Parrable), Bradford Cross (DCVC), Kyle Wild (Keen IO), Tasso Argyros (‎ActionIQ)
This panel brings together partners from some of the world’s leading startup accelerators and founders of up-and-coming enterprise data startups to discuss how we can help create the next generation of successful enterprise data companies. Read more.
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1:15pm1:55pm Wednesday, September 27, 2017
Location: 1E 12/13 Level: Non-technical
Alysa Z. Hutnik (Kelley Drye & Warren LLP)
Big data promises enormous benefits for companies. But what about privacy, data protection, and consumer laws? Having a solid understanding of the legal and self-regulatory rules of the road are key to maximizing the value of your data while avoiding data disasters. Alysa Hutnik shares legal best practices and practical tips to avoid becoming a big data “don’t.” Read more.
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1:15pm1:55pm Wednesday, September 27, 2017
Location: 1A 18 Level: Advanced
Milind Nagnur (Citigroup)
Milind discusses next generation platform , from controlled exploratory sandboxes to hosting transactional applications, and discusses how modern, industry-leading data management tools & self-service analytics can solve this requirement. Read more.
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2:05pm2:45pm Wednesday, September 27, 2017
Location: 1E 12/13
Ashish Verma (Deloitte)
Ashish Verma explores the challenges organizations face after investing in hardware and software to power their analytics projects and the missteps that lead to inadequate data practices. Ashish explains how to course-correct and implement an insight-driven organization (IDO) framework that enables you to derive tangible value from your data faster. Read more.
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2:05pm2:45pm Wednesday, September 27, 2017
Location: 1A 18 Level: Intermediate
Secondary topics:  Financial services, Platform
Nandu Jayakumar (Visa), Ewa Ding (Cloudera)
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 Ewa Ding share Visa’s journey along with some best practices for organizations migrating workloads to Hadoop. Read more.
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2:05pm2:45pm Wednesday, September 27, 2017
Location: 1E 10/11
Michael Dauber (Amplify Partners), Sarah Catanzaro (Canvas Ventures), Katherine Boyle (General Catalyst), Lisha Li (Amplify 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. Read more.
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2:55pm3:35pm Wednesday, September 27, 2017
Location: 1E 10/11 Level: Beginner
Secondary topics:  AI, Marketing
Elsie Kenyon (Nara Logics)
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.
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2:55pm3:35pm Wednesday, September 27, 2017
Location: 1A 18 Level: Intermediate
Secondary topics:  Financial services
Tobi Bosede (Johns Hopkins)
Whether an entity seeks to create trading algorithms or mitigate risk, predicting trade volume is an important task. Focusing on futures trading that relies on Apache Spark for processing the large amount data, Tobi Bosede considers the use of penalized regression splines for trade volume prediction and the relationship between price volatility and trade volume. Read more.
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2:55pm3:35pm Wednesday, September 27, 2017
Location: 1E 12/13
Andy Mauro (Automat)
In this briefing Andy Mauro will explain why the last 15 years of digital marketing has really been about monitoring customers and how recent advancements in artificial intelligence and the dominance of messaging as the primary consumer channel provide an opportunity to achieve every marketers dream of simply talking the their customers. Read more.
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4:35pm5:15pm Wednesday, September 27, 2017
Location: 1E 10/11 Level: Intermediate
Secondary topics:  Healthcare
Charles Boicey (Clearsense)
Charles Boicey explains how Clearsense uses Spark Streaming to provide real-time updates to healthcare providers for critical healthcare needs, helping clinicians make timely decisions from the assessment of a patient's risk based on information gathered from streaming physiological monitoring along with streaming diagnostic data and the patient historical record. Read more.
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4:35pm5:15pm Wednesday, September 27, 2017
Location: 1E 12/13
Edd Wilder-James (Silicon Valley Data Science)
Edd Wilder-James outlines a road map for executives who are beginning to consider their strategies for implementing artificial intelligence in their critical processes. Read more.
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4:35pm5:15pm Wednesday, September 27, 2017
Location: 1A 18 Level: Intermediate
Brendan Aldrich (Ivy Tech Community College ), Lige Hensley (Ivy Tech Community College )
As the largest community college in the US, Ivy Tech ingests over 100M rows of data a day. Brendan Aldrich and Lige Hensley explain how Ivy Tech is applying predictive technologies to establish a true data democracy—a self-service data analytics environment empowering thousands of users each day to improve operations, achieve strategic goals, and support student success. Read more.
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5:25pm6:05pm Wednesday, September 27, 2017
Location: 1E 10/11 Level: Non-technical
Secondary topics:  Marketing, Retail
Karen Moon (Trendalytics), Marta Jamrozik (Claire), Jared Schiffman (Perch Interactive)
In a panel discussion, Karen Moon, Jared Schiffman, and Marta Jamrozik explore how the retail industry is embracing data to include consumers in the design and development process, tackling the challenges associated with the wealth of sources and the unstructured nature of the data they handle and process and how the data is turned into insights that are digestible and actionable. Read more.
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5:25pm6:05pm Wednesday, September 27, 2017
Location: 1E 12/13
Jason McIntyre (Accenture), Mark Milazzo (Accenture)
Whether you are a technology or a services provider, understanding your value in the ecosystem and focusing on the right partners to reach your market goals is critical. Jason McIntyre and Mark Milazzo share examples of teaming models and leading practices for accelerating value from your ecosystem strategy. Read more.
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5:25pm6:05pm Wednesday, September 27, 2017
Location: 1A 18 Level: Advanced
Jerrard Gaertner (University of Toronto)
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.
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9:35am9:50am Thursday, September 28, 2017
Location: 3E
Joanna Bryson (University of Bath | Princeton Center for Information Technology Policy)
AI has been with us for hundreds of years; there's no "singularity" step change. Joanna Bryson explains that the main threat of AI is not that it will do anything to us but what we are already doing to each other with it—predicting and manipulating our own and others' behavior. Read more.
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10:20am10:35am Thursday, September 28, 2017
Location: 3E
danah boyd (Microsoft Research | Data & Society)
Keynote with danah boyd Read more.
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10:35am10:45am Thursday, September 28, 2017
Location: 3E
Tim O'Reilly (O'Reilly Media)
Robots are going to take our jobs, they say. Tim O'Reilly says, "Only if that's what we ask them to do!" Tim has had his fill of technological determinism. He explains why technology is the solution to human problems, and we won't run out of work till we run out of problems. Read more.
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11:20am12:00pm Thursday, September 28, 2017
Location: 1A 18 Level: Beginner
Evan Levy (SAS)
While few would argue the need for a organizations to have a comprehensive data strategy, few have actually developed a strategy and plan to address to improve the access, sharing, and usage of data. Evan Levy discusses the five essential components that make up a data strategy and explores the individual attributes of each. Read more.
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11:20am12:00pm Thursday, September 28, 2017
Location: 1E 12/13
Hilary Mason (Fast Forward Labs)
Progress in machine learning has led us to believe we might soon be able to build machines that talk to us using the same interfaces that we use to talk to each other: natural language. But how close are we? Hilary Mason explores the current state of natural language technologies and some applications where this technology is thriving today and imagines what we might build in the next few years. Read more.
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11:20am12:00pm Thursday, September 28, 2017
Location: 1E 10/11 Level: Beginner
David Boyle (BBC Worldwide)
Too many brilliant analytical minds are wasted on interesting but ultimately less-impactful problems. They are stuck in the weeds of the data or the challenges of our day to day. Too few ask what it means to reach for the stars—the big, shiny, business-changing issues. David Boyle explains why you must start asking bigger questions and making a bigger difference. Read more.
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1:15pm1:55pm Thursday, September 28, 2017
Location: 1A 18 Level: Intermediate
Secondary topics:  Media
Michael Li (LinkedIn), Chi-Yi Kuan (LinkedIn)
Michael Li and Chi-Yi Kuan offer an overview of the EOI framework for big data analytics and explain how to leverage this framework to drive and grow business in key corporate functions, such as product, marketing, and sales. Read more.
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1:15pm1:55pm Thursday, September 28, 2017
Location: 1E 10/11 Level: Intermediate
Secondary topics:  Architecture, Media, Platform
Kurt Brown (Netflix)
Kurt Brown explains how to get the most out of your data infrastructure with 20 principles and practices used at Netflix. Kurt covers each in detail and explores how they interact with the technologies used at Netflix, including S3, Spark, Presto, Druid, R, Python, and Jupyter. Read more.
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1:15pm1:55pm Thursday, September 28, 2017
Location: 1E 12/13
Mike Olson (Cloudera)
Mike Olson shares examples of real-world machine learning applications, explores a variety of challenges in putting these capabilities into production—the speed with with technology is moving, cloud versus in-data-center consumption, security and regulatory compliance, and skills and agility in getting data and answers into the right hands—and outlines proven ways to meet them. Read more.
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2:05pm2:45pm Thursday, September 28, 2017
Location: 1A 18 Level: Intermediate
Francesca Lazzeri (Microsoft), Hong Lu (Microsoft)
New machine learning technologies allow companies to apply better staffing strategies by taking advantage of historical data. Francesca Lazzeri and Hong Lu share a workforce placement recommendation solution that recommends staff with the best professional profile for new projects. Read more.
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2:05pm2:45pm Thursday, September 28, 2017
Location: 1E 10/11 Level: Non-technical
Sander Kieft (Sanoma Media)
Sanoma has been running big data as a self-service platform for over five years, mainly as a service for business analysts to work directly on the source data. The road to getting business analysts to directly do their analyses on Hadoop was far from smooth. Sander Kieft explores Sanoma's journey and shares some lessons learned along the way. Read more.
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2:05pm2:45pm Thursday, September 28, 2017
Location: 1E 12/13
Carme Artigas (Synergic Partners)
Big data technology is mature, but its adoption by business is slow, due in part to challenges like a lack of resources or the need for a cultural change. Carme Artigas explains why an analytics center of excellence (ACoE), whether internal or outsourced, is an effective way to accelerate the adoption and shares an approach to implementing an ACoE. Read more.
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2:55pm3:35pm Thursday, September 28, 2017
Location: 1A 18 Level: Non-technical
Secondary topics:  Cloud, Financial services
Steven Totman (Cloudera), Siew Choo Soh (DBS Bank), Emmie Watt (Air New Zealand), Zhenxiao Luo (Uber)
Major companies in Australia and New Zealand, including Air New Zealand, Westpac, and ANZ, have been pioneering the adoption of big data technologies like Hadoop. In a panel moderated by Steve Totman, senior execs from these companies share use cases, challenges, and how to be successful Down Under, on the opposite side of the world from where technologies like Hadoop got started. Read more.
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2:55pm3:35pm Thursday, September 28, 2017
Location: 1E 12/13 Level: Non-technical
Organizations need a process and supporting frameworks to become more effective at leveraging data and analytics to transform their business models. Using the Big Data Business Model Maturity Index as a guide, William Schmarzo demonstrates how to assess business value and implementation feasibility with respect to the monetization potential of an organization’s business use cases. Read more.
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2:55pm3:35pm Thursday, September 28, 2017
Location: 1E 10/11 Level: Non-technical
Jesse Anderson (Big Data Institute)
Early project success is predicated on management making sure a data engineering team is ready and has all of the skills needed. Jesse Anderson outlines five of the most common nontechnology reasons why data engineering teams fail. Read more.
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4:35pm5:15pm Thursday, September 28, 2017
Location: 1E 10/11 Level: Non-technical
Tanya Cashorali (TCB Analytics)
Given the recent demand for data analytics and data science skills, adequately testing and qualifying candidates can be a daunting task. Interviewing hundreds of individuals of varying experience and skill levels requires a standardized approach. Tanya Cashorali explores strategies, best practices, and deceptively simple interviewing techniques for data analytics and data science candidates. Read more.
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4:35pm5:15pm Thursday, September 28, 2017
Location: 1E 12/13 Level: Intermediate
Ted Malaska (Blizzard Entertainment), Jonathan Seidman (Cloudera)
Recent years have seen dramatic advancements in the technologies available for managing and processing data. While these technologies provide powerful tools to build data applications, they also require new skills. Ted Malaska and Jonathan Seidman explain how to evaluate these new technologies and build teams to effectively leverage these technologies and achieve ROI with your data initiatives. Read more.
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4:35pm5:15pm Thursday, September 28, 2017
Location: 1A 18 Level: Intermediate
Secondary topics:  Architecture
Philip Russom (TDWI: The Data Warehousing Institute)
Philip Russom explains how a data lake can improve the role of Hadoop in data-driven business management. With the right end-user tools, a data lake can enable self-service data practices that wring business value from big data and modernize and extend programs for data warehousing, analytics, data integration, and other data-driven solutions. Read more.