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

Schedule: Executive Briefing sessions

11:1511:55 Wednesday, 23 May 2018
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.
12:0512:45 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Non-technical
Teresa Tung (Accenture Labs), 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.
14:0514:45 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Beginner
Danielle Dean (Microsoft)
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.
14:5515:35 Wednesday, 23 May 2018
Location: Capital Suite 17 Level: Beginner
Dean Wampler (Lightbend)
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.
16:3517:15 Wednesday, 23 May 2018
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.
17:2518:05 Wednesday, 23 May 2018
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.
11:1511:55 Thursday, 24 May 2018
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.
12:0512:45 Thursday, 24 May 2018
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.
14:0514:45 Thursday, 24 May 2018
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.
14:5515:35 Thursday, 24 May 2018
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.
16:3517:15 Thursday, 24 May 2018
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.