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.

Monday-Tuesday 21-22 May: 2-Day Training (Platinum & Training passes)
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
9:00–12:30 Tuesday, 22 May 2018
General Data Protection Regulation (GDPR) tutorial and ePrivacy introduction
Location: Capital Suite 9 Level: Non-technical
Secondary topics:  Security and Privacy
Aurélie Pols (Mind Your Privacy)
Average rating: *****
(5.00, 1 rating)
Aurélie Pols walks you through a "5+5 pillars" framework for GDPR readiness, explaining what the GDPR means to data-fueled businesses. You'll learn how to attribute responsibility to assure compliance and build toward ethical data practices, minimizing risk for your company while fostering trust with your clients. Read more.
9:00–12:30 Tuesday, 22 May 2018
Measure what matters: How your measurement strategy can reduce opex
Location: Capital Suite 12 Level: Non-technical
Secondary topics:  Visualization, Design, and UX
Radhika Dutt (Radical Product), Geordie Kaytes (Fresh Tilled Soil), Nidhi Aggarwal (Radical Product)
Average rating: ****.
(4.00, 2 ratings)
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. Radhika Dutt, Geordie Kaytes, and Nidhi Aggarwal explain how to align measurement with your product strategy so you can measure what matters for your business. Read more.
9:00–17:00 Tuesday, 22 May 2018
Findata Day
Location: Capital Suite 4
Paul Lashmet (Arcadia Data), Anthony Culligan (SETL), Konrad Sippel (Deutsche Börse), Paul Lynn (Nordea), Mikheil Nadareishvili (TBC Bank), Olaf Hein (ORDIX AG), Robert Passarella (Alpha Features), Louise Beaumont (Publicis Groupe | techUK | NPSO), Alistair Croll (Solve For Interesting), Robert Passarella (Alpha Features), Christina Erlwein-Sayer (OptiRisk Systems), Angelique Mohring (GainX), Saeed Amen (Cuemacro), Gisele Frederick (Zingr.io)
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.
13:30–17:00 Tuesday, 22 May 2018
Managing data science in the enterprise
Location: Capital Suite 14 Level: Intermediate
Dan Enthoven (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. Dan Enthoven outlines a holistic approach to people, process, and technology to build a sustainable competitive advantage. Read more.
11:15–11:55 Wednesday, 23 May 2018
Leveraging public-private partnerships using data analytics for economic insights
Location: Capital Suite 15/16 Level: Non-technical
Secondary topics:  Financial Services
Audrey Lobo-Pulo (Phoensight), Nicholas O'Donnell (LinkedIn)
In October 2017, LinkedIn and the Australian Treasury teamed up to gain a deeper understanding of the Australian labor market through new data insights, which may inform economic policy and directly benefit society. Audrey Lobo-Pulo and Nick O'Donnell share some of the discoveries from this collaboration as well as the practicalities of working in a public-private partnership. Read more.
11:15–11:55 Wednesday, 23 May 2018
Executive Briefing: GDPR—Getting your data ready for heavy, new EU privacy regulations
Location: Capital Suite 17 Level: Intermediate
Secondary topics:  Financial Services, Security and Privacy
Mark Donsky (Okera), Syed Rafice (Cloudera)
Average rating: ****.
(4.00, 1 rating)
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 and Syed Rafice outline the capabilities your data environment needs to simplify compliance with GDPR and future regulations. Read more.
12:05–12:45 Wednesday, 23 May 2018
The app trap: Why every mobile app and mobile operator needs anomaly detection
Location: Capital Suite 15/16 Level: Intermediate
Secondary topics:  Telecom, Time Series and Graphs
Ira Cohen (Anodot)
The mobile world has so many moving parts that a simple change to one element can cause havoc somewhere else, resulting in issues that annoy users and cause revenue leaks. Ira Cohen outlines 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.
12:05–12:45 Wednesday, 23 May 2018
Executive Briefing: Becoming a data-driven enterprise—A maturity model
Location: Capital Suite 17 Level: Non-technical
Teresa Tung (Accenture), Jean-Luc Chatelain (Accenture)
Average rating: ***..
(3.12, 8 ratings)
A data-driven enterprise maximizes the value of its data. But how do enterprises emerging from technology and organization silos get there? Teresa Tung and Jean-Luc Chatelain explain how to create a data-driven enterprise maturity model that spans technology and business requirements and walk you through use cases that bring the model to life. Read more.
14:05–14:45 Wednesday, 23 May 2018
Executive Briefing: Lessons learned managing data science projects—Adopting a team data science process
Location: Capital Suite 17 Level: Beginner
Danielle Dean (iRobot)
Average rating: ****.
(4.80, 5 ratings)
Danielle Dean covers the basics of managing data science projects, including the data science lifecycle, and offers an overview of an internal approach at Microsoft called the Team Data Science Process (TDSP). Join in to 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.
14:55–15:35 Wednesday, 23 May 2018
Successful data cultures: Inclusivity, empathy, retention, and results
Location: Capital Suite 15/16 Level: Non-technical
Kim Nilsson (Pivigo), Phil Harvey (Microsoft)
Average rating: ****.
(4.67, 9 ratings)
Our lives are being transformed by data, changing our understanding of work, play, and health. Every organization can take advantage of this resource, but something is holding us back: us. Kim Nilsson and Phil Harvey explain how to build a successful data culture that embeds data at the heart of every organization through people and delivers success through empathy, communication, and humanity. Read more.
14:55–15:35 Wednesday, 23 May 2018
Executive Briefing: What you need to know about fast data
Location: Capital Suite 17 Level: Beginner
Dean Wampler (Anyscale)
Average rating: ****.
(4.00, 2 ratings)
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.
16:35–17:15 Wednesday, 23 May 2018
Data Collaboratives
Location: Capital Suite 15/16 Level: Intermediate
Jude Mccorry (The Data Lab), Mahmood Adil (NHS National Services Scotland)
Average rating: *****
(5.00, 2 ratings)
Jude McCorry and Mahmood Adil offer 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.
16:35–17:15 Wednesday, 23 May 2018
Executive Briefing: BI on big data
Location: Capital Suite 17 Level: Beginner
Mark Madsen (Teradata), Shant Hovsepian (Arcadia Data)
Average rating: ****.
(4.33, 6 ratings)
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.
17:25–18:05 Wednesday, 23 May 2018
Blind men and elephants: What’s missing from your big data?
Location: Capital Suite 15/16 Level: Non-technical
Richard Goyder (IMC Business Architecture | Scaled Insights), Barry Singleton (IMC Business Architecture)
Average rating: ***..
(3.60, 5 ratings)
Big data analytics tends to focus on what is easily available, which is by and large data about what has already happened, the implicit assumption being that past behavior will predict future behavior. Organizations already possess data they aren’t exploiting. Barry Singleton and Richard Goyder explain how, with the right tools, it can be used to develop far more powerful predictive algorithms. Read more.
17:25–18:05 Wednesday, 23 May 2018
Executive Briefing: Why machine-learned models crash and burn in production and what to do about it
Location: Capital Suite 17 Level: Intermediate
Secondary topics:  Managing and Deploying Machine Learning
David Talby (Pacific AI)
Average rating: ****.
(4.00, 1 rating)
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.
11:15–11:55 Thursday, 24 May 2018
Using Python to analyze financial markets
Location: Capital Suite 15/16
Saeed Amen (Cuemacro)
Average rating: ****.
(4.40, 5 ratings)
Saeed Amen explores Python libraries that can be used at the various stages of financial analysis, including time series analysis, visualization, structuring data, and storing market data. Read more.
11:15–11:55 Thursday, 24 May 2018
Executive Briefing: Machine learning—Why you need it, why it's hard, and what to do about it
Location: Capital Suite 17
Mick Hollison (Cloudera)
Average rating: **...
(2.00, 1 rating)
Mick Hollison 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.
12:05–12:45 Thursday, 24 May 2018
On the limits of decision making with artificial intelligence
Location: Capital Suite 15/16 Level: Intermediate
Martin Goodson (Evolution AI)
Average rating: ****.
(4.25, 4 ratings)
How can AI become part of our business processes? Should we entrust critical decisions to completely autonomous systems? Drawing on projects from businesses and UK government agencies, Martin Goodson explains how to increase confidence in AI systems and manage the transition to an AI-driven organization. Read more.
12:05–12:45 Thursday, 24 May 2018
Executive Briefing: Artificial intelligence—The next digital frontier?
Location: Capital Suite 17
Louise Herring (McKinsey & Company)
Average rating: *****
(5.00, 1 rating)
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. Louise Herring 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.
14:05–14:45 Thursday, 24 May 2018
Data, AI, and innovation in the enterprise
Location: Capital Suite 15/16 Level: Beginner
Michael Li (The Data Incubator), Philipp Diesinger (Boehringer Ingelheim), Julie Shin (Citigroup)
Average rating: *****
(5.00, 1 rating)
What are the latest initiatives and use cases around data and AI? How are data and AI reshaping industries? How do we foster a culture of data and innovation within a larger enterprise? What are some of the challenges of implementing AI within the enterprise setting? Michael Li moderates a panel of experts in different industries to answer these questions and more. Read more.
14:05–14:45 Thursday, 24 May 2018
Executive Briefing: Data privacy in the age of the internet of things
Location: Capital Suite 17 Level: Beginner
Secondary topics:  Security and Privacy, Telecom
Alasdair Allan (Babilim Light Industries)
The increasing ubiquity of the internet of things has put a new focus on data privacy. Big data is all very well when it's harvested quietly and stealthily, but when your things tattle on you behind your back, it's a very different matter altogether. Alasdair Allan explains why the internet of things brings with it a whole new set of big data problems that can't be ignored. Read more.
14:55–15:35 Thursday, 24 May 2018
The journey of machine learning platform adoption in enterprise
Location: Capital Suite 15/16 Level: Non-technical
Secondary topics:  Data Platforms, Managing and Deploying Machine Learning
Simon Chan (Salesforce)
Average rating: ****.
(4.00, 1 rating)
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 experience helping executives establish AI product strategies, Simon Chan helps you discover the AI platform journey that is right for your business. Read more.
14:55–15:35 Thursday, 24 May 2018
Executive Briefings: Killer robots and how not to do data science
Location: Capital Suite 17 Level: Non-technical
Secondary topics:  Security and Privacy
Kate Vang (DataKind UK), Christine Henry (DataKind UK)
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. DataKind UK is passionate about using machine learning and artificial intelligence for social good. Kate Vang and Christine Henry explain what socially conscious AI looks like and what DataKind is doing to make it a reality. Read more.
16:35–17:15 Thursday, 24 May 2018
The artful science of metrics: Measurements that work
Location: Capital Suite 15/16 Level: Intermediate
Tags: us
Ketan Gangatirkar (Indeed)
Average rating: *****
(5.00, 1 rating)
Quantitative measurement is the key to scaling businesses, processes, and products and making them better. It sounds easy: just pick a number and improve it. However, actually choosing a metric is an exploration of a many-dimensional space with no map and no guide. Until now. Join Ketan Gangatirkar to learn how to choose the right metrics so you can build a better product and a better business. Read more.
16:35–17:15 Thursday, 24 May 2018
Executive Briefing: The ROI of data-driven digital transformation
Location: Capital Suite 17 Level: Intermediate
Kevin Sigliano (IE Business School )
Average rating: *****
(5.00, 1 rating)
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.