Programme List - Big Data & IoT Summit
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Programme

8:30–9:00
Registration and breakfast
9:00–9:10
Welcome and opening remarks
Stuart Sumner, Editorial Director, Computing, V3 & The Inquirer
9:10–9:25
Computing research. View from the foothills of the Internet of Things
Peter Gothard, Technology Analyst, Incisive Media
  • How prepared are organisations to exploit the potential of the IoT? What steps are they taking?
  • The alignment of the IoT and Big Data tools
  • The problem of 'fake data'
  • Data Scientists vs Data Analysts
9:25–9:55
Opening keynote:
Big Data at CERN's Large Hadron Collider
Dr Jamie Shiers, Data Preservation Project Leader, CERN
  • Currently data is generated at a rate of around 50 PB a year after highly de-selective triggers. The total data volume is expected to reach around 10EB by the time data taking completes in the mid to late 2030s
  • Collecting, distributing and processing such vast amounts of data
  • Turning data into discoveries - Higgs boson case study
  • Data preservation and curation for future re-use: what is the business case, the technical solutions deployed and how these might be offered as fully generic services in the nascent European Open Science Cloud
9:55-10:20
Case study:
From concrete and cars to Big data and telepathy: how to build Smart Cities
Dr Rick Robinson, Director of Technology, Amey
  • Amey provides services that are used by millions of people every day to live, work and travel; but the way that we live, work and travel is being transformed by intelligent infrastructure, the digitisation of public services, and the emergence of "platform" business models such as Uber and Airbnb.
  • In this talk I'll describe how we're exploring the capabilities, maturity, business benefits and investment risks of these technologies; the challenges of integrating them into a large and complex business; and how the right sort of partnerships can "create the conditions for success" for a 21st century digital society

Have you say! Interactive poll I
10:20-11:00
Polylogue (discussion stimulated by the audience):
Implementing business change with the help of Big Data analytics
Gael Decoudu, Head of Data Science, Shop Direct
Paul Pardoe, Business Architect, BGL
Dr Kevin Findlay, Former IT & Digital Board Director, Complete Cover Group
Jude Mc Corry, Head of Business Development, The Data Lab
Moderator: Graeme Burton, Group News Editor, Incisive Business Enterprise IT
  • What business change has Big Data brought to your business?
11:00-11:30
Morning break, networking and visit to the exhibition area

Have you say! Interactive poll II
11:30-11:50
The Enterprise Immune System: using machine learning for next-generation cyber defense
Peppa Wise, Senior Account Manager, Darktrace
  • Using machine learning and AI algorithms to defend against advanced cyber-threats
  • How to pre-empt emerging threats and reduce incident response time
  • Achieving 100% network visibility with the 3D Threat Visualizer
  • Real-world case studies of subtle, unknown cyber-threats detected by ‘immune system' technology
11:50-12:30
Polylogue (discussion stimulated by the audience):
Big Data skills and culture
Tristan Isles, Solution Development Manager, Honda
Tom Dalglish, Head Of Technical Services - Applied Innovation, HSBC
Robert Tulloch, Director European Hospital Products, DRG Decision Resources Group
Kaspar Gering, Data Scientist, TransferWise
Moderator: Stuart Sumner, Editorial Director, Computing, V3 & The Inquirer
  • Is having creative/innovative insights a key to success with Big Data/IoT? Why?
12:30-13:30
Lunch, networking and visit to the exhibition area

STRATEGIC TRACK


Have you say! Interactive poll III
13:30-13:55
Case study:
Data science in the enterprise
Dr Nicholas Williams, Big Data & Machine Learning Senior SME, Lloyds Banking Group
  • Big Data for data science
  • The journey deploying machine learning on Big Data
  • The challenges for an enterprise
  • The divide between innovation and production
13:55-14:20
Case study:
Exploiting new opportunities that Business Intelligence brings
John Kundert, CTO, Financial Times
  • Understanding the difference between information and intelligence
  • How to gain competitive advantage with the help of BI?
  • Challenges when interpreting data and how to tackle them
14:20-14:45
Case study:
Lessons learned: introducing data science into a traditional business
Dr Miranda Chong, Data Science Manager, Rank Group
  • What were the strategic objectives behind Rank's introduction of data science?
  • What candidate profile has Rank decided to target? What was the prior experience of the team and how they have applied it to Rank's business challenges?
  • What has been achieved so far, the key challenges, and the plans for the future
14:45-15:10
Case study:
Data science in a mission driven organisation
Marcus Atkinson, Product Analyst, TransferWise
Tom Hillman, Performance Marketing Manager, TransferWise
  • The role of quantitative and qualitative analytics in getting us to where we are now
  • Culture in TransferWise
  • Understanding viral growth

TECHNICAL TRACK


Have you say! Interactive poll III
13:30-13:55
Case study:
Chatbots - staying ahead of your competitors
Dr Natalia Konstantinova, Lead Software Engineer (R&D), First Utility
  • How chatbots can help you decrease costs and improve customer service
  • How can your company benefit from the help of AI?
  • What challenges you face when adopting AI
13:55-14:20
Case study:
Turning big data into life-saving and profitable tools
Dr Huseyin Seker, Director of Enterprise and Engagement, Northumbria University
  • Understanding data mining methods that help drive actionable knowledge from very high-dimensional data sets
  • Dealing with very high-dimensional data sets with quantitative outcomes - how to address this challenge in the big data era
  • Covering real-world (successful) examples of both academic and industrial projects that we are working on within our research teams (Bio-Health Informatics and Big Data Analytics Lab)
14:20-14:45
Case study:
Building scalable Product Analytics platform from scratch
Dr Jelena Isachenkova, Technical Project Lead, Badoo
  • This talk will uncover how we organised Product Analytics solution as a single point of truth at Badoo that today tracks 300m users on 5 different client platforms and several products in a unified way
  • Product Analytics aims to help understand users' journeys and their behavior patterns through event data on a detailed level
  • High event variety challenges analytics and end users with finding the right data and metadata for their questions
  • Additionally, we will present how metadata management and abstraction tools can help boost the agility and scalability of the team performance
14:45-15:10
Case study:
What are the first steps to take that will help make Big Data implementation a success?
Michael Pollett, Software Engineer, Skyscanner
  • Our learnings from spending a year building the wrong data processing system
  • Planning your requirements with use-cases
  • What the Skyscanner data platform looks like today
15:10-15:30
Afternoon break, networking and visit to the exhibition area

Have you say! Interactive poll IV
15:30-16:00
Case study:
Successful management of Big Data projects at the European Space Agency
Dr Redouane Boumghar, Research Fellow in Data Science for Space Operations, European Space Agency
  • Data-driven decision making
  • Mapping the skills of your team and how staff interact
  • The importance of the disruption of hierarchy
  • The hidden benefits of being open
  • Access the space industry in a new way with the Libre Space Foundation
16:00-16:50
Panel discussion:
Data explosion – how not to get lost
Scott Krueger, Data Architect, Skyscanner
Tom Kennedy, Global Head of Analytics, Thomson Reuters
Tom Heath, Data and Systems Architect, Arup
Omar Khan, Data and Technology Director, MEC Global
Carolyn Stebbings, Senior Vice President Data & Technology Solutions, RAPP
Moderator: Peter Gothard, Technology Analyst, Incisive Business Enterprise Technology
  • How not to get lost in large quantity of data?
  • Do we need that much data? Are there limits to data driven decision making?
  • Do you believe the data we currently give away for free should carry standardised financial value for individuals? How do you put monetary value on data?
16:50-16:55
Closing remarks
Stuart Sumner, Editorial Director, Computing, V3 and The Inquirer