Programme @


Big Data Analytics

16 June 2022

Millennium Gloucester Conference Centre, London

Programme @ BDA

Morning Session

moving forward in a data-driven way with your users, customers and business working together

  • Data in motion: moving your data at the speed of business
  • From the edge to the cloud and everywhere in between
  • What’s out there? Marrying your disparate data sources
  • From vendor to in-house – How to reimagine your analytics landscape
  • Graph data science: what can it do for you?
  • Getting to know your customers

09:00 (BST)

Conference Chair's Opening Address

Dr Gilad Rosner
Founder, IoT Privacy Forum; Expert in Public Policy of IoT & Identity Management; Privacy and Technology Policy Researcher
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Dr Gilad Rosner, Founder, IoT Privacy Forum; Expert in Public Policy of IoT & Identity Management; Privacy and Technology Policy Researcher

09:10 (BST)

How to create a real competitive advantage with technology?

Elvys Nunes
Global Head of Category Insights and Analytics, Reckitt
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Elvys Nunes, Global Head of Category Insights and Analytics, Reckitt

Insights, intelligence, and analytics teams face more challenges than ever before: tight budgets, more demand and lack of resources.

You need to find the right tech partner to solve a business need or bring a competitive advantage to your business.

• What are the challenges of choosing the right technology for your industry?
• How to master insights processes with partnerships?

09:25 (BST)

From the edge to the cloud and everywhere in between

Organisations are forever searching for new and innovative ways to share and collaborate on data in order to maximise the value it has to the business.

Such a preoccupation has only served to become an obsession thanks to the enforced workforce distribution of the pandemic.

One such transformative way in which to do so is with a cutting-edge data cloud centre.

We address:

  • Why data cloud over other platforms?
  • Its architecture, structure and performance value
  • How it can match workload size and scalability challenges

09:40 (BST)

How are making complex financial decisions easy through using data (Simples!).

Maaike Van Den Branden
Associate Director - Data Insights & Analytics,
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Maaike Van Den Branden, Associate Director – Data Insights & Analytics,

Offering price comparisons for over 20 insurance, financial and digital products, has collected a lot of customer data from a large part of the UK adult population over the years.

Sorting out financial household management is perceived as a hassle by many of us, so is using that data to make customers’ lives easier and do some of the heavy liftings for them.

In this presentation we would like to share some of the journeys CtM has been on:

• How we realised that customers weren’t interested in more tools to help them, they needed some of the work taken away from them

• How we decided that our technical landscape had to change to accomplish this

• How a change in the company-wide operating model supported a test and learn approach to achieve this ambition

• How machine learning techniques allowed us to become more relevant to our customers

• How bringing people together changed the dynamics and speed of delivery of our company

• How we formed our dream team to enable this

09:55 (BST)

Working at Government Scale

Andrew Morgan
Director of Data, 6point6
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Andrew Morgan, 6point6

Join this session to find out how you can succeed with data assurance at scale.

We address the challenge with data profiling tools and explain how we’ve been working to deliver data quality at scale with the UK Government.

10:10 (BST)

Sky Finance Analytics Case Study

Rajiv Chandra
Head of Finance Analytics, Sky
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Yixiang Dong
Head of Finance in cost Analytics, Sky
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Rajiv Chandra, Head of Finance Analytics, Sky

Yixiang Dong, Head of Finance in cost Analytics, Sky

10:25 (BST)

Questions to the Panel of Speakers

10:35 (BST)

Refreshment Break Served in the Exhibition Area

11:05 (BST)

Welcome to Session Two

11:10 (BST)

Why Organizations are Reframing Location Intelligence

Helen McKenzie
Geospatial Advocate, CARTO
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Helen McKenzie, Geospatial Advocate, CARTO

CARTO’s Helen McKenzie will share why organizations are reframing Location Intelligence with the use of global hierarchical grids such as H3, S2 and Quadkey. She’ll share how this type of geographic index – along with cloud-native data warehouses – can enable analysis of spatial “big data” that would previously have taken days, or not even be possible at all. We’ll look at some real-world examples CARTO & hierarchical grids in action, focusing on retail and logistics in London.

11:25 (BST)

Delivering a holistic picture of the business

Christina Finlay
Director, Data & Analytics, Nest
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Christina Finlay, Director, Data & Analytics, Nest

We address, using data to break down organisational silos, how to make data a team sport, and drive simplicity in reporting.

11:35 (BST)

Case Study: Getting to know your customers with AI

Getting to know your customers from a naked revenue generating perspective, customer personalisation matters above all else.

Product recommendations, messaging, timing, discounts, promotions, offers and home pages, all play a role in not just retaining your customer base, but also in upselling, cross selling and repeat business.

With an AI-driven personalised product platform, you can make your business more relevant, noticeable, and successful.

Join us as we highlight how you can reorganise your business around AI and machine learning.

11:50 (BST)

Questions to the Panel of Speakers

12:05 (BST)

Delegates Move to Seminar Rooms

12:15 (BST)

Seminar Sessions

13:00 (BST)

Networking Lunch Served in the Exhibition Area

Afternoon Session

Solution Provider Customer Case Study Session

  • Why the democratisation of data accessibility matters?
  • Modernise your IA
  • Building assurance into your ML production pipeline
  • Predict and optimise your business outcomes
  • Fighting misinformation with big data and AI
  • Data governance as a business enabler
  • Mitigate risk and accelerate insights

14:00 (BST)

Conference Chair’s Afternoon Address

14:05 (BST)

Retail Industry Case Study: The Power of Data in Motion at Sainsbury's

Anna Semjen
Solutions Engineer, Confluent
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Anna Semjen, Solutions Engineer, Confluent

Many businesses have come to the realisation that customer expectations have radically changed, and they expect their requests to be fulfilled in real-time. Join Confluent to discover how companies such as Sainsbury are using data in motion to meet customer expectations and deliver results, including:

• Notable cost savings across the entire supply chain

• Doubled efficiency of engineering development thanks to real-time data streams

• 20+ hours of sprint time saved with managed support from Confluent

14:20 (BST)

Security Industry Case Study: How LexisNexis® ThreatMetrix® is using near real-time analytics to reduce transaction fraud for global brands by verifying customer identity

Matthias Baumhof
CTO, ThreatMetrix Business Services LexisNexis Risk Solutions
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Matthias Baumhof CTO, ThreatMetrix LexisNexis Risk Solutions

ThreatMetrix® uses analytics to verify identities and reduce fraud as a transaction occurs, supporting thousands of global brands across tens of thousands of web properties.

  • Learn how ThreatMetrix overcame performance and reliability challenges by switching to Yellowbrick for their real-time analytics needs, transforming their product offering
  • Understand how ThreatMetrix operates at high performance, low latency and at a massive scale

14:35 (BST)

Banking Industry Case Study: Linking Data Governance to Business Goals in Practice

Jean-Paul Otte
Chief Data Officer, Degroof Petercam
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Jean-Paul Otte, Chief Data Officer, Degroof Petercam 

In this session, Jean Paul Otte – Chief Data Officer- will share how Degroof Petercam successfully implemented its data governance strategy.

Join and learn more about:

• Ensuring trusted and governed data
• Enabling implementation of an harmonised data environment
• Materialising data value through BI and Analytics       Enablement
• Initiating a concrete working approach
• Implementing a business-driven data management process

14:50 (BST)

Questions to the Panel of Speakers

15:05 (BST)

Afternoon Networking and Refreshments served in the Exhibition Area

15:35 (BST)

Welcome back

15:40 (BST)

AI: Buy vs Build

Joe Murfin
Lead Data Scientist, Saint Gobain
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Joe Murfin, Lead Data Scientist, Saint Gobain

In 2022 there is a wide variety of data science and AI solutions on the market. Many solutions already exist to cover most common needs so when should you purchase an off the shelf data science and AI solutions and when should you consider building in-house?

• The landscape of data and AI solutions
• Buy – purchasing an AI solution (pros and cons)
• Build – making an AI solution (pros and cons)
• What is most appropriate in which scenario?

15:55 (BST)

Case Study: Predict and optimise your business outcomes

Data is essential, but true optimisation comes from improving performance and competitive advantage from the production of analytics models which allow for democratic access to the insights gained.

Many believe that the best approach to producing an effective model starts with the identification of a business opportunity which allows you to determine how the model can improve performance, rather than starting with the data.

We address how such an approach to modelling can generate faster outcomes and embed models in practical data relationships that are more accessible and how this approach avoids the potential of designing overly complex models which exhaust organisational capabilities.

16:10 (BST)

Measuring and evidencing the value of diversity and social mobility in data and analytics recruitment

Jeremiah Gogo
Head of Data & A&R Analytics, Atlantic Records
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Jeremiah Gogo, Head of Data & A&R Analytics, Atlantic Records

16:25 (BST)

Questions to the Panel of Speakers

16:40 (BST)

Conference Chair Closing Remarks

16:45 (BST)

Conference Closes

Please note:
Whitehall Media reserve the right to change the programme without prior notice.

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