Featured Speakers
Platinum pass holders have access to Strata Business Summit Mon–Thurs. Gold and Silver pass holders have access to Strata Business Summit on Tues–Thurs. Bronze pass holders have access to Strata Business Summit on Wed–Thurs.
Monday-Tuesday, September 23-24: 2-Day Training (Platinum & Training passes) |
Tuesday, September 24: Tutorials (Gold & Silver passes) |
Wednesday, September 25: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes) |
8:45am | Location: 3E Strata Data Conference Keynotes |
10:50
Morning break |
Thursday, September 26: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes) |
8:45am | Location: 3E Strata Data Conference Keynotes |
10:50 Morning break |
9:00am - 5:00pm Monday, September 23 & Tuesday, September 24
Location: 1A 01/02
Michael Li and Gonzalo Diaz provide a nontechnical overview of AI and data science. Learn common techniques, how to apply them in your organization, and common pitfalls to avoid. You’ll pick up the language and develop a framework to be able to effectively engage with technical experts and use their input and analysis for your business’s strategic priorities and decision making.
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9:00am–12:30pm Tuesday, September 24, 2019
Location: 1A 10
Creating and leading a successful ML strategy is an elegant orchestration of many components: master key ML concepts, operationalize ML workflow, prioritize highest-value projects, build a high-performing team, nurture strategic partnerships, align with the company’s mission, etc. Rossella Blatt Vital details insights and lessons learned in how to create and lead a flourishing ML practice.
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1:30pm–5:00pm Tuesday, September 24, 2019
Location: 1A 10
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 must deliver measurable impact on an increasing share of an enterprise’s KPIs. The speakers explore how leading organizations take a holistic approach to people, process, and technology to build a sustainable advantage.
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11:20am–12:00pm Wednesday, September 25, 2019
Location: 1E 10/11
Machine learning and data science systems often fail in production in unexpected ways. David Talby outlines 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.
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11:20am–12:00pm Wednesday, September 25, 2019
Location: 1E 12/13
While data science value is well recognized within tech, experience across industries shows that the ability to realize and measure business impact is not universal. A core issue is that data science programs face unique risks many leaders aren’t trained to hedge against. Brian Dalessandro addresses these risks and advocates for new ways to think about and manage data science programs.
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11:20am–12:00pm Wednesday, September 25, 2019
Location: 1E 14
Join Data & Society Research Institute Executive Director Janet Haven for a deep dive into research, case studies and emerging governance approaches to creating the rules of ethical AI.
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1:15pm–1:55pm Wednesday, September 25, 2019
Location: 1E 10/11
As a steward for your enterprise’s data and digital transformation initiatives, you’re tasked with making the right choice. But before you can make those decisions, it’s important to understand what not to do when planning for your organization’s big data initiatives. Michael Stonebraker shares his top 10 big data blunders.
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1:15pm–1:55pm Wednesday, September 25, 2019
Location: 1E 12/13
Geotab is a world-leading asset-tracking company with millions of vehicles under service every day. Felipe Hoffa and Bob Bradley examine the challenges and solutions to create an ML- and geographic information system- (GI)S enabled petabyte-scale data warehouse leveraging Google Cloud. And they dive into the process to publish open, how you can access it, and how cities are using it.
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1:15pm–1:55pm Wednesday, September 25, 2019
Location: 1E 14
Machine learning techniques are being deployed across almost every industry and sector. But this adoption comes with real, and oftentimes underestimated, privacy and security risks. Andrew Burt and Brenda Leong convene a panel of experts including David Florsek, Chris Wheeler, and Alex Beutel to detail real-life examples of when ML goes wrong, and the lessons they learned.
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2:05pm–2:45pm Wednesday, September 25, 2019
Location: 1E 10/11
Every organization wants to use data more effectively and as a weapon, but few succeed. Arup Nanda explores how Priceline started on this journey and how it was successful using different techniques and tools. Join in to learn how to streamline data assets, make it easier for end users, define KPIs, create value from data, and build sponsorships to build a data organization.
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2:05pm–2:45pm Wednesday, September 25, 2019
Location: 1E 12/13
Despite a meteoric rise in data volumes within modern enterprises, enabling nontechnical users to put this data to work in diagnostic and predictive tasks remains a fundamental challenge. Peter Bailis details the lessons learned in building new systems to help users leverage the data at their disposal, drawing on production experience from Facebook, Microsoft, and the Stanford DAWN project.
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2:05pm–2:45pm Wednesday, September 25, 2019
Location: 1E 14
From the EU to California and China, more of the world is regulating how data can be used. Andrew Burt and Brenda Leong convene leading experts on law and data science for a deep dive into ways to regulate the use of AI and advanced analytics. Come learn why these laws are being proposed, how they’ll impact data, and what the future has in store.
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2:55pm–3:35pm Wednesday, September 25, 2019
Location: 1E 10/11
We're living in a culture obsessed with predictions. In politics and business, we collect data in service of the obsession. But our need for certainty and control leads some organizations to be duped by unproven technology or pseudoscience—often with unforeseen societal consequences. Farrah Bostic looks at historical—and sometimes funny—examples of sacrificing understanding for "data."
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2:55pm–3:35pm Wednesday, September 25, 2019
Location: 1E 12/13
Tim McKenzie examines why planning 5G network rollout and associated services requires a good understanding of location-based data. Accurate addressing and linking consumers to property or points of interest allows data enrichment with attributes, demographics and social data. Companies use location to organize and analyze network and customer data to understand where to target new services.
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2:55pm–3:35pm Wednesday, September 25, 2019
Location: 1E 14
The fear that comes along with new compliance requirements is overwhelming. Organizations don’t know where to start, what to fix, or what an auditor expects to see. Mark Hinely gives you an auditor's perspective on the newest security and privacy regulations, how your business can prepare for compliance, and what the audit looks like to an auditor.
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4:35pm–5:15pm Wednesday, September 25, 2019
Location: 1E 10/11
Andrew Brust provides a primer on data catalogs and a review of the major vendors and platforms in the market. He examines the use of data catalogs with classic and newer data repositories, including data warehouses, data lakes, cloud object storage, and even software and applications. You'll learn about AI's role in the data catalog world and get an analysis of data catalog futures.
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4:35pm–5:15pm Wednesday, September 25, 2019
Location: 1E 12/13
While regulations affect your life every day, and millions of public comments are submitted to regulatory agencies in response to their proposals, analyzing the comments has traditionally been reserved for legal experts. Vlad Eidelman outlines how natural language processing (NLP) and machine learning can be used to automate the process by analyzing over 10 million publicly released comments.
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4:35pm–5:15pm Wednesday, September 25, 2019
Location: 1E 14
Elasticsearch (ES) allows extremely quick search and drilldowns on large amounts of semistructured data. Elasticsearch, however, does not have relational join capabilities. Giovanni Tummarello examines a plug-in for ES that adds cluster distributed joins and demonstrates how it enables an exciting array of use cases dealing with interconnected or "Knowledge Graph" enterprise data.
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5:25pm–6:05pm Wednesday, September 25, 2019
Location: 1E 10/11
The arrival of a new generation of smart embedded hardware may cause the demise of large-scale data harvesting. In its place, smart devices will let us process data at the edge and extract insights without storing potentially privacy and GDPR infringing data. Join Alasdair Allan to learn why the current age where privacy is no longer "a social norm" may not long survive the coming of the IoT.
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5:25pm–6:05pm Wednesday, September 25, 2019
Location: 1E 12/13
Brazil deployed a national biometric system to register all Brazilian voters using multiple biometric modalities and to ensure that a person does not enroll twice. This session highlights how a large-scale biometric system works, and what are the main architecture decisions that one has to take in consideration.
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5:25pm–6:05pm Wednesday, September 25, 2019
Location: 1E 14
There's a lack of standard for the collection of gender data. Brindaalakshmi K takes a look at the implications of such a lack in the context of a developing country like India, the exclusion of individuals beyond the binary genders of male and female, and how this exclusion permeates beyond the public sector into private sector services.
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11:20am–12:00pm Thursday, September 26, 2019
Location: 1E 10/11
Gayle Bieler explains how she built a thriving center for data science within a large, well-respected nonprofit research institute and shares some of its most impactful projects and best adventures to date, that have solved important national problems, improved local communities, and transformed research.
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11:20am–12:00pm Thursday, September 26, 2019
Location: 1E 12/13
Language shapes our thinking, our relationships, our sense of self. Conversation connects us in powerful, intimate, and often unconscious ways. Jonathan Foster explains why, as we design for natural language interactions and more humanlike digital experiences, language—as design material, conversation, and design canvas—reveals ethical challenges we couldn't encounter with GUI-powered experiences.
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11:20am–12:00pm Thursday, September 26, 2019
Location: 1E 14
As an early adopter of data science, machine learning, and AI, Deutsche Bank's analytics function is trailblazing new ways to drive revenues, lower costs, and reduce risk across all areas of the group. John Allen shares how his team combines commercial offerings with open source technologies to revolutionize legacy processes and transform the way the bank uses technology to drive innovation.
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1:15pm–1:55pm Thursday, September 26, 2019
Location: 1E 10/11
This talk will explore some of the philosophy around the concept of explaining a model given the colloquial definition is partially recursive. It will cover the lens banking regulation places on this philosophical basis and expand into techniques used for these well governed aspects.
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1:15pm–1:55pm Thursday, September 26, 2019
Location: 1E 12/13
If you've ever been confused about what it takes to be a data scientist or curious about how companies recruit, train, and manage analytics resources, Usama Fayyad and Hamit Hamutcu are here to explore insights from the most comprehensive research effort to date on the data analytics profession and propose a framework for the standardization of roles and methods for assessing skills.
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1:15pm–1:55pm Thursday, September 26, 2019
Location: 1E 14
Miscommunication between business leaders and technical experts can doom even the best data science project. Don’t let it drive you insane! In this session, we’ll dissect many flavors of communication failure, from goal misalignment to technical misunderstanding. Then, we’ll explore practical ways to bridge these gaps.
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2:05pm–2:45pm Thursday, September 26, 2019
Location: 1E 10/11
Paco Nathan outlines the history and landscape for vendors, open source projects, and research efforts related to AutoML. Starting from the perspective of an AI expert practitioner who speaks business fluently, Paco unpacks the ground truth of AutoML—translating from the hype into business concerns and practices in a vendor-neutral way.
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2:05pm–2:45pm Thursday, September 26, 2019
Location: 1E 12/13
T-Mobile successfully improved the quality of voice calling by analyzing crowdsourced big data from mobile devices. Alex Yoon walks you through how engineers from multiple backgrounds collaborated to achieve 10% improvement in voice quality and why the analysis of big data was the key to the success in bringing a better voice call service quality to millions of end users.
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2:05pm–2:45pm Thursday, September 26, 2019
Location: 1E 14
Failures or issues in a product or service can negatively affect the business. Detecting issues in advance and recovering from them is crucial to keeping the business alive. Join Akshay Rai to learn more about LinkedIn's next-generation open source monitoring platform, an integrated solution for real-time alerting and collaborative analysis.
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3:45pm–4:25pm Thursday, September 26, 2019
Location: 1E 10/11
Jonathan Tudor and Ross Schalmo explore how GE Aviation made it a mission to implement self-service data. To ensure success beyond initial implementation of tools, the data engineering and analytics teams created initiatives to foster engagement from an ongoing partnership with each part of the business to the gamification of tagging data in a data catalog to forming a published dataset council.
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3:45pm–4:25pm Thursday, September 26, 2019
Location: 1E 14
As new digital platforms emerge and governments look at new ways to engage with citizens, there's an increasing awareness of the role these platforms play in shaping public participation and democracy. Audrey Lobo-Pulo, Annette Hester, and Ryan Hum examine the design attributes of civic engagement technologies and their ensuing impacts and an NEB Canada case study.
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3:45pm–4:25pm Thursday, September 26, 2019
Location: 1E 12/13
At MakeMyTrip customers were using voice or email to contact agents for postsale support. In order to improve the efficiency of agents and improve customer experience, MakeMyTrip developed a chatbot, Myra, using some of the latest advances in deep learning. Madhu Gopinathan and Sanjay Mohan explain the high-level architecture and the business impact Myra created.
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4:35pm–5:15pm Thursday, September 26, 2019
Location: 1E 10/11
Dean Wampler dives into how (and why) to integrate ML into production streaming data pipelines and to serve results quickly; how to bridge data science and production environments with different tools, techniques, and requirements; how to build reliable and scalable long-running services; and how to update ML models without downtime.
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4:35pm–5:15pm Thursday, September 26, 2019
Location: 1E 14
California is following the EU's GDPR with the California Consumer Protection Act (CCPA) in 2020. Penalties for non-compliance, but many companies aren't prepared for this strict regulation.
This session will explore the capabilities your data environment needs in order to simplify CCPA and GDPR compliance, as well as other regulations.
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4:35pm–5:15pm Thursday, September 26, 2019
Location: 1E 12/13
Companies that harness creativity and data in tandem have growth rates twice as high as companies that don’t. David Boyle shares lessons from his successes and failures in trying to do just that across presidential politics, with pop stars, and with power brands in the world of luxury goods. Join in to find out how analysts can work differently to build these partnerships and unlock this growth.
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