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

March 6-8, 2018
San Jose, CA

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.

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.

Featured Speakers

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 March 6: Tutorials (Gold & Silver passes)
Wednesday March 7: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes)
8:45 | Location: Salon 1&2
Strata Data Conference Keynotes
10:30am
Morning break
Thursday March 8: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes)
8:45 | Location: Salon 1&2
Strata Data Conference Keynotes
10:30am
Morning break
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9:00am12:30pm Tuesday, March 6, 2018
Location: LL20 C Level: Beginner
Burcu Baran (LinkedIn), Wei Di (LinkedIn), Michael Li (LinkedIn), Chi-Yi Kuan (LinkedIn)
Burcu Baran, Wei Di, Michael Li, and Chi-Yi Kuan walk you through the big data analytics and data science lifecycle and share their experience and lessons learned leveraging advanced analytics and machine learning techniques such as predictive modeling to drive and grow business at LinkedIn. Read more.
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9:00am5:00pm Tuesday, March 6, 2018
Location: LL20 A
Mike Prorock (mesur.io)
Hear practical insights from household brands and global companies: the challenges they tackled, approaches they took, and the benefits—and drawbacks—of their solutions. Read more.
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9:00am5:00pm Tuesday, March 6, 2018
Location: LL20 B
Ray Bernard (SuprFanz), Jennifer Webb (SuprFanz)
Hear from innovators in ad tech, measurement, automation, and audience engagement about where the media industry is today—and where it's likely to go next. Read more.
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1:30pm5:00pm Tuesday, March 6, 2018
Location: LL20 C Level: Non-technical
Nick Elprin (Domino Data Lab)
The honeymoon era of data science is ending, and accountability is coming. Not content to wait for results that may or may not arrive, successful data science leaders deliver measurable impact on an increasing share of an enterprise's KPIs. Nick Elprin details how leading organizations have taken a holistic approach to people, process, and technology to build a sustainable competitive advantage. Read more.
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11:00am11:40am Wednesday, March 7, 2018
Location: LL21 C/D Level: Intermediate
Mark Madsen (Third Nature)
If your goal is to provide data to an analyst rather than a data scientist, what’s the best way to deliver analytics? There are 70+ BI tools in the market and a dozen or more SQL- or OLAP-on-Hadoop open source projects. A panel of experts details the trade-offs between a number of architectures that provide self-service access to data. Read more.
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11:00am11:40am Wednesday, March 7, 2018
Location: LL21 E/F Level: Intermediate
Anne Buff (SAS Institute)
Emerging technologies such as the IoT, AI, and ML present businesses with enormous opportunities for innovation, but to maximize the potential of these technologies, businesses must radically shift their approach to governance. Anne Buff explains what it takes to shift the focus of governance from standards, conformity, and control to accountability, extensibility, and enablement. Read more.
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11:00am11:40am Wednesday, March 7, 2018
Location: 230 A Level: Intermediate
Mauro Damo (Dell), wei lin (Dell EMC)
Image recognition classification of diseases will improve and support physicians decisions, minimize the possibility of medical mistakes, improve patient treatment, and speed up patient diagnosis. Mauro Damo and Wei Lin offer an overview of a convolutional neural network model to classify MRI images of bladder cancer into the four classes of primary tumors. Read more.
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11:50am12:30pm Wednesday, March 7, 2018
Location: LL21 C/D Level: Non-technical
Yishay Carmiel (IntelligentWire | Spoken Labs)
One of the most important tasks of AI has been to understand humans. People want machines to understand not only what they say but also what they mean and to take particular actions based on that information. This goal is the essence of conversational AI. Yishay Carmiel explores the latest breakthroughs and revolutions in this field and the challenges still to come. Read more.
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11:50am12:30pm Wednesday, March 7, 2018
Location: LL21 E/F Level: Beginner
Matthew Granade (Domino Data Lab)
Predictive analytics and artificial intelligence have become critical competitive capabilities. Yet IT teams struggle to provide the support data science teams needs to succeed. Matthew Granade explains how leading banks, insurance and pharmaceutical companies, and others manage data science at scale. Read more.
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1:50pm2:30pm Wednesday, March 7, 2018
Location: LL21 C/D Level: Non-technical
Frances Haugen (Pinterest), Patrick Phelps (Pinterest)
Data science is most powerful when combined with deep domain knowledge, but those with domain knowledge don't work on data-focused teams. So how do you empower employees with diverse backgrounds and skill sets to be effective users of data? Frances Haugen and Patrick Phelps dive into the social side of data and share strategies for unlocking otherwise unobtainable insights. Read more.
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1:50pm2:30pm Wednesday, March 7, 2018
Location: LL21 E/F Level: Beginner
Paco Nathan (O'Reilly Media)
Human in the loop (HITL) has emerged as a key design pattern for managing teams where people and machines collaborate. Such systems are mostly automated, with exceptions referred to human experts, who help train the machines further. Paco Nathan offers an overview of HITL from the perspective of a business manager, focusing on use cases within O'Reilly Media. Read more.
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1:50pm2:30pm Wednesday, March 7, 2018
Location: 230 A Level: Beginner
Ayin Vala (Foundation for Precision Medicine)
Complex diseases like Alzheimer’s cannot be cured by pharmaceutical or genetic sciences alone, and current treatments and therapies lead to mixed successes. Ayin Vala explains how to use the power of big data and AI to treat challenging diseases with personalized medicine, which takes into account individual variability in medicine intake, lifestyle, and genetic factors for each patient. Read more.
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2:40pm3:20pm Wednesday, March 7, 2018
Location: LL21 C/D
Michael Chui (McKinsey Global Institute)
After decades of extravagant promises, artificial intelligence is finally starting to deliver real-life benefits to early adopters. However, we're still early in the cycle of adoption. Michael Chui explains where investment is going, patterns of AI adoption and value capture by enterprises, and how the value potential of AI across sectors and business functions is beginning to emerge. Read more.
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2:40pm3:20pm Wednesday, March 7, 2018
Location: 230 A Level: Beginner
Or Herman-Saffar (Dell), Ran Taig (Dell)
What if we could predict when and where next crimes will be committed? Or Herman-Saffar and Ran Taig offer an overview of Crimes in Chicago, a publicly published dataset of reported incidents of crime that have occurred in Chicago since 2001. Or and Ran explain how to use this data to explore committed crimes to find interesting trends and make predictions for the future. Read more.
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4:20pm5:00pm Wednesday, March 7, 2018
Location: LL21 C/D 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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4:20pm5:00pm Wednesday, March 7, 2018
Location: 230 A Level: Intermediate
Kapil Surlaker (LinkedIn), Ya Xu (LinkedIn)
Metrics measurement and experimentation plays a crucial role in every product decision at LinkedIn. Kapil Surlaker and Ya Xu explain why, to meet the company's needs, LinkedIn built the UMP and XLNT platforms for metrics computation and experimentation, respectively, which have allowed the company to perform measurement and experimentation very efficiently at scale while preserving trust in data. Read more.
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5:10pm5:50pm Wednesday, March 7, 2018
Location: LL21 C/D
Alysa Z. Hutnik (Kelley Drye & Warren LLP), Crystal Skelton (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 and Crystal Skelton share legal best practices and practical tips to avoid becoming a big data “don’t.” Read more.
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5:10pm5:50pm Wednesday, March 7, 2018
Location: LL21 E/F Level: Non-technical
Angela Zutavern (Booz Allen Hamilton)
How can you most effectively use machine intelligence to drive strategy? By merging it in the right way with the human ingenuity of leaders throughout your organization. Angela Zutavern shares insights from her work with pioneering companies, government agencies, and nonprofits that are successfully navigating this partnership by becoming “mathematical corporations.” Read more.
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11:00am11:40am Thursday, March 8, 2018
Location: LL21 C/D
Mike Olson (Cloudera)
Mike Olson shares examples of real-world machine learning applications, explores a variety of challenges in putting these capabilities into production—including 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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11:00am11:40am Thursday, March 8, 2018
Location: LL21 E/F Level: Beginner
Michael Schrenk (Self-Employed)
Big data becomes much more powerful when it has context. Fortunately, creative data scientists can create needed context though the use of metadata. Michael Schrenk explains how metadata is created and used to gain competitive advantages, predict troop strength, or even guess Social Security numbers. Read more.
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11:00am11:40am Thursday, March 8, 2018
Location: 230 A Level: Beginner
Sugreev Chawla (Thorn)
Sugreev Chawla offers an overview of Spotlight, a tool created by Thorn, a nonprofit that uses technology to fight online child sexual exploitation. It allows law enforcement to process millions of escort ads per month in an effort to fight sex trafficking, using graph analysis, time series analysis and NLP techniques to surface important networks of ads and characterize their behavior over time. Read more.
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11:50am12:30pm Thursday, March 8, 2018
Location: LL21 C/D Level: Intermediate
David Talby (Pacific AI)
Machine learning and data science systems often fail in production in unexpected ways. David Talby shares real-world case studies showing why this happens and explains what you can do about it, covering best practices and lessons learned from a decade of experience building and operating such systems at Fortune 500 companies across several industries. Read more.
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11:50am12:30pm Thursday, March 8, 2018
Location: LL21 E/F Level: Beginner
John Mertic (The Linux Foundation), Ferd Scheepers (ING)
John Mertic and Ferd Scheepers detail the benefits of a vendor-neutral approach to data governance, explain the need for an open metadata standard, and share insight around how companies ING, IBM, Hortonworks, and more are delivering solutions to this challenge as an open source initiative. Read more.
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11:50am12:30pm Thursday, March 8, 2018
Location: 230 A Level: Intermediate
With so many business intelligence tools in the Hadoop ecosystem and no common measure to identify the efficiency of each tool, where do you begin to build or modify your enterprise data lake strategy? Sagar Kewalramani shares real-world BI problems and how they were resolved with Hadoop tools and demonstrates how to build an effective data lake strategy with open source tools and components. Read more.
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1:50pm2:30pm Thursday, March 8, 2018
Location: LL21 C/D Level: Intermediate
Mark Donsky (Cloudera)
In May 2018, the General Data Protection Regulation (GDPR) goes into effect for firms doing business in the EU, but many companies aren't prepared for the strict regulation or fines for noncompliance (up to €20 million or 4% of global annual revenue). Mark Donsky outlines the capabilities your data environment needs to simplify compliance with GDPR and future regulations. Read more.
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1:50pm2:30pm Thursday, March 8, 2018
Location: 230 A Level: Intermediate
Michael Lysaght (Weight Watchers), Steven Levine (Weight Watchers ), Nicolas Chikhani (Weight Watchers)
For organizations stuck in a myriad of legacy infrastructure, the path to AI and deep learning seems impossible. Michael Lysaght, Steven Levine, and Nicolas Chikhani discuss Weight Watchers's transition from a traditional BI organization to one that uses data effectively, covering the company's needs, the changes that were required, and the technologies and architecture used to achieve its goals. Read more.
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2:40pm3:20pm Thursday, March 8, 2018
Location: LL21 E/F Level: Beginner
Brian Karfunkel (Pinterest)
When software companies use A/B tests to evaluate product changes and fail to accurately estimate the long-term impact of such experiments, they risk optimizing for the users they have at the expense of the users they want to have. Brian Karfunkel explains how to estimate an experiment’s impact over time, thus mitigating this risk and giving full credit to experiments targeted at noncore users. Read more.
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2:40pm3:20pm Thursday, March 8, 2018
Location: 230 A Level: Beginner
Matt Derda (Trifacta), Jonathon Whitton (PRGX USA)
PRGX is a global leader in recovery audit and source-to-pay (S2P) analytics services, serving around 75% of the top 20 global retailers. Matt Derda and Jonathon Whitton explain how PRGX uses Trifacta and Cloudera to scale current processes and increase revenue for the products and services it offers clients. Read more.
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4:20pm5:00pm Thursday, March 8, 2018
Location: LL21 E/F Level: Beginner
Mike Driscoll (Metamarkets)
There’s a make-or-break step ahead for AI development. AI tools shouldn’t be designed to replace humans; they should be built with them in mind. We need to focus on translating data from machine learning models into beautiful, intuitive visuals. Mike Driscoll shares advice for creators of next-gen predictive algorithms from his experience turning big data into interactive visualizations. Read more.
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4:20pm5:00pm Thursday, March 8, 2018
Location: 230 A Level: Beginner
Marcin Pilarczyk (Ryanair)
Managing fuel at a company flying 120 millions passengers yearly is not a trivial task. Marcin Pilarczyk explores the main aspects of fuel management of a modern airline and offers an overview of machine learning methods supporting long-term planning and daily decisions. Read more.