Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
Strata Business Summit

29 April-2 May 2019
London, UK

Alistair Croll, Strata Conference Chair

Make data work for business.

The 2019 Strata Business Summit will give you a thorough understanding of how some of the world’s leading companies build successful data strategies. You’ll discover game-changing technologies and their business applications—and how to move your enterprise forward to bridge the gap. You'll also receive a hand-picked lineup of executive briefings on key issues such as: predictive analytics and machine learning, Cloud strategy, governance security and privacy, IoT, and artificial intelligence, and more.

Strata Business Summit provides the intel you need to build strategies and data-driven business models that deliver customer insight, drive efficiency and innovation in products and services, modernize architecture, reduce costs, and lower risk.

Featured Speakers

Platinum pass holders have access to 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 29 April - Tuesday 30 April: 2-Day Training (Platinum & Training passes)
Tuesday 30 April: Tutorials (Gold & Silver passes)
Wednesday 1 May: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes)
8:45 | Location: Ballroom
Strata Data Conference Keynotes
10:30
Morning break
Thursday 2 May: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes)
8:45 | Location: Ballroom
Strata Data Conference Keynotes
10:30
Morning break
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9:00 - 17:00 Monday, 29 April & Tuesday, 30 April
Location: Capital Suite 17
Secondary topics:  AI and machine learning in the enterprise
Angie Ma (ASI Data Science)
Angie Ma and Jonny Howell offer a condensed introduction to key AI and machine learning concepts and techniques, showing you what is (and isn't) possible with these exciting new tools and how they can benefit your organization. Read more.
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9:0017:00 Tuesday, 30 April 2019
Location: Capital Suite 12
Alistair Croll (Solve For Interesting)
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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9:0017:00 Tuesday, 30 April 2019
Location: Capital Suite 13
From analyzing risk and detecting fraud to predicting payments and improving customer experience, take a deep dive into the ways data technologies are transforming the financial industry. Read more.
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13:3017:00 Tuesday, 30 April 2019
Location: Capital Suite 8
Secondary topics:  AI and machine learning in the enterprise
Peter Aiken (Data BluePrint, DAMA International, Virginia Commonwealth University)
The presents a more operational perspective on the use of data strategy that is especially useful for organizations just getting started with data Read more.
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11:1511:55 Wednesday, 1 May 2019
Location: Capital Suite 10/11
Secondary topics:  Security and Privacy
Mark Hinely (KirkpatrickPrice)
Organizations across the globe are trying to determine whether GDPR applies to them. Now, it seems as though GDPR principles are headed to the US. In 2018 alone, more ten states have passed or amended consumer privacy and breach notification laws. Mark Hinely will provide insight on the current and future data privacy laws in the US and how they will impact organizations across the globe. Read more.
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11:1511:55 Wednesday, 1 May 2019
Location: Capital Suite 13
Secondary topics:  AI and Data technologies in the cloud, AI and machine learning in the enterprise, IoT and its applications
Mike Olson (Cloudera)
It's easier than ever to collect data -- but managing it securely, in compliance with regulations and legal constraints is harder. There are plenty of tools that promise to bring machine learning techniques to your data -- but choosing the right tools, and managing models and applications in compliance with regulation and law is quite difficult. Read more.
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12:0512:45 Wednesday, 1 May 2019
Location: Capital Suite 10/11
Secondary topics:  AI and machine learning in the enterprise, Ethics
Laila Paszti (GTC Law Group PC & Affiliates)
As companies commercialize novel applications of AI in areas such as finance, hiring, and public policy, there is concern that these automated decision-making systems may unconsciously duplicate social biases, with unintended societal consequences. This talk will provide practical advice for companies to counteract such prejudices through a legal and ethics based approach to innovation. Read more.
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12:0512:45 Wednesday, 1 May 2019
Location: Capital Suite 12
Secondary topics:  Data Platforms, Retail and e-commerce
Dirk Petzoldt (Zalando SE)
Case Study from Europe’s leading online fashion platform Zalando about its journey to a scalable, personalized Machine Learning based marketing platform. Read more.
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12:0512:45 Wednesday, 1 May 2019
Location: Capital Suite 13
Secondary topics:  AI and machine learning in the enterprise, Open Data, Data Generation and Data Networks
Peter Skomoroch (Workday)
Companies that understand how to apply machine intelligence will scale and win their respective markets over the next decade. Others will fail to ship successful AI products that matter to customers. This talk describes how to combine product design, machine learning, and executive strategy to create a business where every product interaction benefits from your investment in machine intelligence. Read more.
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14:0514:45 Wednesday, 1 May 2019
Location: Capital Suite 10/11
Secondary topics:  AI and machine learning in the enterprise, Ethics
Duncan Ross (TES Global), Francine Bennett (Mastodon C)
Being good is hard. Being evil is fun and gets you paid more. Once more Duncan Ross and Francine Bennett explore how to do high-impact evil with data and analysis (and possibly AI). Make the maximum (negative) impact on your friends, your business, and the world—or use this talk to avoid ethical dilemmas, develop ways to deal responsibly with data, or even do good. But that would be perverse. Read more.
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14:0514:45 Wednesday, 1 May 2019
Location: Capital Suite 13
Secondary topics:  Data preparation, data governance, and data lineage, Security and Privacy
Mark Donsky (Okera)
General Data Protection Regulation (GDPR) goes into effect in May 2018 for firms doing any business in the EU. However many companies aren't prepared for the strict regulation or fines for noncompliance (up to €20 million or 4% of global annual revenue). This session will explore the capabilities your data environment needs in order to simplify GDPR compliance, as well as future regulations. Read more.
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14:5515:35 Wednesday, 1 May 2019
Location: Capital Suite 10/11
Secondary topics:  Data Platforms, Transportation and Logistics, Visualization, Design, and UX
Our experience with building the Business Intelligence platform has been nothing short of extraordinary. The proposal contains details about how Uber thought about building it's Business Intelligence platform. In this talk, I’ll narrate the journey of deciding on how we took a platform approach rather than adding features in a piecemeal fashion. Read more.
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14:5515:35 Wednesday, 1 May 2019
Location: Capital Suite 12
David Maman (Binah.ai)
The combination of a mere of a few minutes of video, signal processing, remote heart rate monitoring, machine learning, and data science can identify a person’s emotions, health condition and performance. Financial institutions and potential employers can analyze whether you have good or bad intentions. Read more.
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14:5515:35 Wednesday, 1 May 2019
Location: Capital Suite 13
Secondary topics:  AI and machine learning in the enterprise, Data preparation, data governance, and data lineage
Paco Nathan (derwen.ai)
Data governance is an almost overwhelming topic. This talk surveys history, themes, plus a survey of tools, process, standards, etc. Mistakes imply data quality issues, lack of availability, and other risks that prevent leveraging data. OTOH, compliance issues aim to preventing risks of leveraging data inappropriately. Ultimately, risk management plays the "thin edge of the wedge" in enterprise. Read more.
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16:3517:15 Wednesday, 1 May 2019
Location: Capital Suite 10/11
Secondary topics:  Visualization, Design, and UX
Brian O'Neill (Designing for Analytics)
Gartner says 85%+ of big data projects will fail, despite the fact your company may have invested millions on engineering implementation. Why are customers and employees not engaging with these products and services? Brian O'Neill explains why a "people first, technology second" mission—a design strategy, in other words—enables the best UX and business outcomes possible. Read more.
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16:3517:15 Wednesday, 1 May 2019
Location: Capital Suite 12
Secondary topics:  Data preparation, data governance, and data lineage, Financial Services, Security and Privacy
Maurício Lins (everis consultancy UK), Lidia Crespo (Santander UK)
Big data is usually regarded as a menace for data privacy. However, with the right principles and mind-set, it can be a game changer to put customers first and consider data privacy an inalienable right. Santander UK applied this model to comply with GDPR by using graph technology, Hadoop, Spark, Kudu to drive data obscuring and data portability, and driving machine learning exploration. Read more.
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16:3517:15 Wednesday, 1 May 2019
Location: Capital Suite 13
Ellen Friedman (MapR Technologies)
A surprising fact of modern technology is that not knowing some things can make you better at what you do. This isn’t just lack of distraction or being too delicate to face reality. It’s about separation of concerns, with a techno flavor. In this talk I go through five things that best practice with emerging technologies and new architectures can give us ways to not know, and why that’s important. Read more.
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17:2518:05 Wednesday, 1 May 2019
Location: Capital Suite 10/11
Secondary topics:  Visualization, Design, and UX
Mars Geldard (University of Tasmania), Paris Buttfield-Addison (Secret Lab Pty. Ltd.)
Science-fiction has been showcasing complex, AI-driven (often AR or VR) interfaces (for huge amounts of data!) for decades. As television, movies, and video games became more capable of visualising a possible future, the grandeur of these imagined science fictional interfaces has increased. What can we learn from Hollywood UX? Is there a useful takeaway? Does sci-fi show the future of AI UX? Read more.
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17:2518:05 Wednesday, 1 May 2019
Location: Capital Suite 12
Secondary topics:  Ethics
Duncan Ross (TES Global), Giselle Cory (DataKind)
DataKind UK has been working in data for good since 2013 working with over 100 uk charities, helping them to do data science for the benefit of their users. Some of those projects have delivered above and beyond expectations - others haven't. In this session Duncan and Giselle will talk about how to identify the right data for good projects... Read more.
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11:1511:55 Thursday, 2 May 2019
Location: Capital Suite 12
Secondary topics:  Health and Medicine
Fabio Ferraretto (Accenture), Tatiane Canero (Hospital Albert Einstein)
How Albert Einstein and Accenture evolved patient flow experience and efficiency with the use of applied AI, statistics and combinatorial math, allowing the hospital to antecipate E2E visibility within patient flow operations, from admission of emergency and ellective demands, to assignment and medical releases. Read more.
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11:1511:55 Thursday, 2 May 2019
Location: Capital Suite 13
Secondary topics:  AI and machine learning in the enterprise, Transportation and Logistics
Brandy Freitas (Pitney Bowes)
Data science is an approachable field given the right framing. Often, though, practitioners and executives are describing opportunities using completely different languages. In this session, Harvard Biophysicist-turned-Data Scientist, Brandy Freitas, will work with participants to develop context and vocabulary around data science topics to help build a culture of data within their organization. Read more.
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12:0512:45 Thursday, 2 May 2019
Location: Capital Suite 12
Secondary topics:  AI and machine learning in the enterprise
Vidya Raman (Cloudera)
Not surprisingly, there is no single approach to embracing data-driven innovations within any industry vertical. However, there are some enterprises that are doing a better job than others when it comes to establishing a culture, process and infrastructure that lends itself to data-driven innovations. In this talk, we will share some key foundational ingredients that span multiple industries. Read more.
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12:0512:45 Thursday, 2 May 2019
Location: Capital Suite 13
Secondary topics:  IoT and its applications, Security and Privacy
Alasdair Allan (Babilim Light Industries)
A arrival of new generation of smart embedded hardware may cause the demise of large scale data harvesting. In its place smart devices will allow us process data at the edge, allowing us to extract insights from the data without storing potentially privacy and GDPR infringing data. The current age where privacy is no longer "a social norm" may not long survive the coming of the Internet of Things. Read more.
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14:0514:45 Thursday, 2 May 2019
Location: Capital Suite 12
Secondary topics:  AI and machine learning in the enterprise
Rosaria Silipo (KNIME)
This is a collection of past data science projects. While the structure is often similar - data collection, data transformation, model training, deployment - each one of them has needed some special trick. It was either the change in perspective or a particular techniques to deal with special case and special business questions the turning point in implementing the data science solution. Read more.
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14:5515:35 Thursday, 2 May 2019
Location: Capital Suite 12
Secondary topics:  AI and machine learning in the enterprise
Robert Cohen (Economic Strategy Institute)
This talk describes the skills that employers are seeking from employees in digital jobs – linked to the new software hierarchy driving digital transformation. We describe this software hierarchy as one that ranges from DevOps, CI/CD, and microservices to Kubernetes and Istio. This hierarchy is used to define the jobs that are central to data-driven digital transformation. Read more.
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14:5515:35 Thursday, 2 May 2019
Location: Capital Suite 13
Secondary topics:  AI and Data technologies in the cloud
Nikki Rouda (Amazon Web Services (AWS))
This talk is about some of the key trends we see in data lakes and analytics, and how they shape the services we offer at AWS. Specific topics include the rise of machine generated data and semi-structured/unstructured data as dominant sources of new data, the move towards serverless, SPI-centric computing, and the growing need for local access to data from users around the world. Read more.
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16:3517:15 Thursday, 2 May 2019
Location: Capital Suite 12
Secondary topics:  Ethics, Security and Privacy
Sundeep Reddy Mallu (Gramener Inc)
Answering simple question of what rights do Indian citizens have over their data is a nightmare. The rollout of India Stack technology based solutions has added fuel to fire. Sundeep explains, with on ground examples, how businesses and citizens are navigating the India Stack ecosystem while dealing with Data privacy, security & Ethics space in India's booming digital economy. Read more.
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16:3517:15 Thursday, 2 May 2019
Location: Capital Suite 13
Secondary topics:  Data Integration and Data Pipelines, Streaming and realtime analytics
Dean Wampler (Lightbend)
Your team is building Machine Learning capabilities. I'll discuss how you can integrate these capabilities in streaming data pipelines so you can leverage the results quickly and update them as needed. There are big challenges. How do you build long-running services that are very reliable and scalable? How do you combine a spectrum of very different tools, from data science to operations? Read more.