Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Strata Business Summit

22-24 May 2018
London, UK

Make data work for business.

The 2018 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.

In just 3 days, you’ll have 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

Gold and Silver pass holders have access to Strata Business Summit on Tues–Thurs. Platinum and Bronze pass holders have access to Strata Business Summit on Wed–Thurs.

Tuesday 22 May: Tutorials (Gold & Silver passes)
Wednesday 23 May: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes)
9:00 | Location: Auditorium
Strata Data Conference Keynotes
10:45
Morning break
Thursday 24 May: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes)
9:00 | Location: Auditorium
Strata Data Conference Keynotes
10:45
Morning break
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9:0012:30 Tuesday, 22 May 2018
Location: Capital Suite 8 Level: Non-technical
Radhika Dutt (Radical Product), Geordie Kaytes (Fresh Tilled Soil), Nidhi Aggarwal (Radical Product)
These days it’s easy for companies to say, "We measure everything!” The problem is, most “popular” metrics may not be appropriate or relevant for your business. Measurement isn’t free, and should be done strategically. This session covers how you can align measurement with your product strategy, so you can measure what matters for your business. Read more.
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9:0012:30 Tuesday, 22 May 2018
Location: Capital Suite 9 Level: Non-technical
Secondary topics:  Security and Privacy
Aurélie Pols (Mind Your Privacy)
Using a 5+5 Pillars Framework for GDPR Readiness, this tutorial walks attendees through what the GDPR means to data fueled businesses. Anchored within the accountability principle, this interactive session allows to attribute responsibility to assure compliance and hopefully build towards ethical data practices, minimizing risk for your company while fostering trust with your clients. Read more.
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13:3017:00 Tuesday, 22 May 2018
Location: Capital Suite 8 Level: Intermediate
Nick Elprin (Domino Data Lab)
The honeymoon era of data science is ending: 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 enterprises’ KPIs. You’ll learn how leading organizations take a holistic approach to people, process, and technology to build a sustainable competitive advantage. Read more.
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11:1511:55 Wednesday, 23 May 2018
Location: Capital Suite 15/16 Level: Non-technical
Audrey Lobo-Pulo (The Australian Treasury), Nick O'Donnell (LinkedIn), Jacinta Greenwell (The Australian Treasury)
In October 2017, LinkedIn and the Australian Treasury teamed up to gain a deeper understanding of the Australian labour market through new data insights which may inform economic policy and directly benefit society. This presentation shares some of the discoveries, together with the practicalities of working in a public-private partnership. Read more.
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11:1511:55 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Intermediate
Secondary topics:  Security and Privacy
Mark Donsky (Cloudera)
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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12:0512:45 Wednesday, 23 May 2018
Location: Capital Suite 15/16 Level: Intermediate
Ira Cohen (Anodot)
The mobile world has so many moving parts, so a simple change to one element can cause havoc somewhere else. Resulting issues can annoy users and cause revenue leaks. This presentation will discuss ways to use anomaly detection to track everything mobile, from the service and roaming to specific apps, to fully optimize your mobile offerings. Read more.
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12:0512:45 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Non-technical
Teresa Tung (Accenture Labs), Jean-Luc Chatelain (Accenture)
A data-driven enterprise maximizes the value of its data. But how do enterprises emerging from technology and organization silos get there? We use our experience helping our clients through this journey to create a data-driven enterprise maturity model that spans technology and business requirements. We will walk through use cases that bring the model to life. Read more.
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14:0514:45 Wednesday, 23 May 2018
Location: Capital Suite 15/16 Level: Beginner
In-house data science teams often work with a range of business functions, apply diverse techniques and face unpredictable hurdles related to requirements, data, infrastructure and deployment. Traditional data science processes are too abstract to cope with the complexity of these environments. This session will use recent project examples at easyJet to highlight how we overcame these challenges. Read more.
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14:0514:45 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Beginner
Danielle Dean (Microsoft)
This presentation covers the basics of managing data science projects, including the data science lifecycle and overview of one example approach that is adopted internally at Microsoft called the "Team Data Science Process" (TDSP). Learn more about the typical priorities of data science teams and the keys to success on engaging and creating value with data science. Read more.
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14:5515:35 Wednesday, 23 May 2018
Location: Capital Suite 15/16 Level: Non-technical
Kim Nilsson (Pivigo), Phil Harvey (Microsoft)
Our lives are being transformed by data. Our work, our play and our health are now understood in new ways. Every organisation can take advantage of this resource. But something is holding us back; us! This talk discusses how to build a successful data culture. To embed data at the heart of every organization through people. How empathy, communication and humanity delivers success. Read more.
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14:5515:35 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Beginner
Dean Wampler (Lightbend)
Streaming data systems, so called fast data, promise accelerated access to information, leading to new innovations and competitive advantages. But they aren't just faster versions of big data. They force architecture changes to meet new demands for reliability and dynamic scalability, more like microservices. Dean Wampler outlines what you need to know to exploit fast data successfully. Read more.
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16:3517:15 Wednesday, 23 May 2018
Location: Capital Suite 15/16 Level: Intermediate
Jude Mccorry (The Data Lab)
Jude Mccorry offers an overview of Data Collaboratives, a new form of collaboration beyond the public-private partnership model, in which participants from different sectors  exchange data, skills, leadership, and knowledge to solve complex problems facing children in Scotland and worldwide. Read more.
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16:3517:15 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Beginner
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. Mark Madsen and Shant Hovsepian discuss the trade-offs between a number of architectures that provide self-service access to data. Read more.
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17:2518:05 Wednesday, 23 May 2018
Location: Capital Suite 15/16 Level: Non-technical
Stuart Sherman (IMC Busiess Architecture), Richard Goyder (IMC Business Architecture & Scaled Insights)
Analytics using big data tends to focus on what is easily available, which is, by and large, data about what has already happened. The implicit assumption is that past behaviour will predict future behaviour. In this presentation we will show how organizations already possess data they aren’t exploiting that, with the right tools, can be used to develop far more powerful predictive algorithms. Read more.
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17:2518:05 Wednesday, 23 May 2018
Location: Capital Suite 17 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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11:1511:55 Thursday, 24 May 2018
Location: Capital Suite 17
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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12:0512:45 Thursday, 24 May 2018
Location: Capital Suite 15/16 Level: Intermediate
Martin Goodson (Evolution AI)
How can AI become part of our business processes? Should we entrust critical decisions to completely autonomous systems? I’ll illustrate how to increase confidence in AI systems and manage the transition to an AI-driven organisation. Examples will be drawn from projects running in enterprise businesses and UK government agencies. Read more.
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14:0514:45 Thursday, 24 May 2018
Location: Capital Suite 15/16 Level: Beginner
Michael Li (The Data Incubator), Sol Rashidi (Royal Caribbean Cruise Lines)
What are the latest initiatives and use cases around Data and AI within different corporations and industries? How are Data and AI reshaping different industries? What are some of the challenges of implementing AI within the enterprise setting? We’re convening four experts from different industries to answer these questions and more! Read more.
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14:0514:45 Thursday, 24 May 2018
Location: Capital Suite 17 Level: Beginner
Secondary topics:  Security and Privacy
Alasdair Allan (Babilim Light Industries)
The current age where privacy is no longer "a social norm" may not long survive the coming of the Internet of Things. Big data is all very well when it is harvested quietly and stealthily. But when your things tattle on you behind your back, it'll be a very different matter altogether. The rush to connect devices to the Internet has led to sloppy privacy controls. That can't continue. Read more.
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14:5515:35 Thursday, 24 May 2018
Location: Capital Suite 15/16 Level: Non-technical
Simon Chan (Salesforce)
The promises of AI are great, but taking the steps to implement AI within an enterprise is challenging. The secret behind enterprise AI success often traces back to the underlying platform that accelerates AI development at scale. Based on years of experiences helping executives establish AI product strategies, Dr. Simon Chan walks through the AI platform journey that is right for your business. Read more.
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14:5515:35 Thursday, 24 May 2018
Location: Capital Suite 17 Level: Non-technical
Kate Vang (DataKind UK), Gianfranco Cecconi (Digital Contraptions Imaginarium Ltd.)
Not a day goes by without reading headlines about the fear of AI or how technology seems to be dividing us more than bringing us together. Here at DataKind UK we're passionate about how machine learning and artificial intelligence can be used for social good. We'll talk about what socially conscious AI looks like, and what we're doing to make it a reality. Read more.
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16:3517:15 Thursday, 24 May 2018
Location: Capital Suite 15/16 Level: Beginner
Daniel Gilbert (News UK), Jonathan Leslie (Pivigo)
In the era of 24-hour news and online newspapers, editors in the newsroom must be able to make fast decisions about their content and must quickly and efficiently make sense of the enormous amounts of data that they encounter. We will discuss an ongoing partnership between News UK and Pivigo in which a team of data science trainees helped develop an AI platform to help in this task. Read more.
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16:3517:15 Thursday, 24 May 2018
Location: Capital Suite 17 Level: Intermediate
Kevin Sigliano (IE Business School )
Financial and consumer ROI demands that business leaders understand the drivers and dynamics of digital transformation and big data. Kevin Sigliano explains why disrupting value propositions and continuous innovation are critical if you wish to dramatically improve the way your company engages customers and creates value and maximize financial results. Read more.