Big Data Analytics

8 March 2018

Postillion Convention Centre Amsterdam



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Session ONE – Utilising Big Data Analytics to Extract Value and Achieve Actionable Business Insights

  • Making Business Sense of Big Data: What does it mean for your enterprise and how can you harness it to add value and improve performance?
  • Identifying trends and patterns of activity in structured and unstructured data to better understand your customers, users, transactions and systems
  • Turning data into new visibility and business intelligence
  • Utilising predictive analytics for impactful action
  • Building an agile, responsive and powerful Big Data architecture
  • Data Science and disruptive emerging trends (AI, Machine Learning, Blockchain, IoT)
Conference Chair’s Opening Address

Professor Marc Salomon, Dean of the Amsterdam Business School (ABS), Director of the MBA in Big Data & Business Analytics and Member of the Big Data Alliance Board

Morning Keynote Address: Extracting Value from Big Data

Tamas Erkelens, Program Manager Data Innovation, City of Amsterdam

Our opening presentation will discuss how the Municipality of Amsterdam uses data to improve citizen services. In Amsterdam, the European Capital of Innovation 2016-2017, digital social innovation is key. In order to connect business, academia and local government to citizens, the city has to address local challenges. With the biggest big data infrastructure in Europe – Amsterdam Exchange – Amsterdam is ready for the artificial intelligence era.


In today’s world, harnessing analytic capabilities to drive business growth is going to be a key differentiator for any enterprise. Companies without plans for managing and exploiting the explosion in data are said to be losing out. In our opening session, we look to address these questions and more, including:

Why is Big Data Analytics becoming so important and what can we do with it? What are the key drivers for Big Data?
How can enterprises establish a roadmap for Big Data implementation, and gather momentum to create a game-changing vision for their business?
What is the potential for Big Data to fuel technological disruption? What impact is it having on emerging technologies (AI, Machine Learning, IoT) and how will it impact the conventional IT department?
How can enterprises provide governance across data when the originating sources may have varying quality and privacy/security constraints?

10 key tips for the Chief Data Officer

Peter Jackson, Chief Data Officer, Southern Water and Co-author of ‘The Chief Data Officer’s Playbook’

Caroline Carruthers, Group Director of Data Management, Lowell Group and Co-author of ‘The Chief Data Officer’s Playbook’

Practical hints, tips and real-world examples from practitioners about how to make your life as a CDO just a little easier

BI to AI: Evolving from Traditional Look-back Analyses to Forward-Thinking Prediction and Prescription

Wael Elrifai, Senior Director of Enterprise Solutions, EMEA & APAC, Hitachi Vantara

This presentation will look at:

• Understanding the business case
• Achievable phase 1 outcomes and timelines
• Core technical infrastructure and skills
• Pitfalls and roadblocks

Data is the new oil. Design your Enterprise for the age of digital disruption

Alejandra Leon, Director, Lead Architect Digital, Architecture & Emerging Technologies, Philips IT

One of the biggest challenges for companies that the digital economy brings is to rapidly respond to constant changes in technology, customer demands and new disruptive business models. To respond effectively, companies must be able to adapt by incorporating data-driven strategies into their platforms, IT landscapes and core business. 

Questions to the Panel of Speakers
Refreshment Break Served in the Exhibition Area
Deploying Next Generation Predictive Analytics

A predictive capacity can lead to better financial results and greater competitive advantage. We explore:

  • Which business functions can use predictive analytics
  • How data is driving the need for forecasting and prediction
  • Decision optimisation and predictive capabilities
  • Common deployments – challenges and successful integrations
  • Areas in which predictive analytics can have significant impact: sales performance monitoring, research and development, customer retention, product profitability and revenue analysis
Big Data in the Travel Industry; Taking the KLM Big Data program from Exploration to Implementation

Cosmando Byarugaba, Program Lead, Big Data Program, Air France-KLM

Creating a Big Data program is a complex task where the definition of a clear vision is imperative. This presentation will lead you through the main steps, from vision definition and experimentation to program implementation. The successful implementation of such a program revolves around many aspects other than only data and technology. Executive Sponsorship, Business Innovation drive, Organizational Transformation as well as Business Leadership are equally crucial to success.

Taming the Data Lake

Massive repositories of data – data lakes – continue to pose several challenges around turning raw data into usable assets. This session highlights how enterprises can tame the turbulence of data lakes, prevent them from becoming data swamps, and overcome challenges associated with data siloes, conflicting objectives, integration, and governance.

A Risk-reduction Perspective on Data Quality and Fit-for-purpose Usability

Michiel van Dongen, Senior Account Manager Data Innovation, Koninklijk Nederlands Meteorologisch Instituut

KNMI is one of the oldest data providers in the world (since 1854). Its mission is to warn and inform society of the risks and threats from the physical environment. KNMIs 24h-operational centre leverages its internationally acclaimed scientific capacities to forecast weather, produce climate scenarios and monitor seismic and infrasound events and air quality. It serves sectors such as defense and aerospace, infrastructure and transport, mobility and public health, agriculture, energy (solar, wind, geothermal, fossil) and utilities.

Today, it ingests about 1500 Gb of raw data per day from sensor networks, satellites, supercomputer generated models and crowd- and alternative sources. Ultimately, the phenomena monitored by KNMI are turned into historic, real-time and forecasting data-products that impact people and their livelihoods, government policy and economic efficiencies. It handles about 2M downloads (~10Tb) per month. As such, it is of paramount importance to understand the opportunities, challenges and limitations of the dynamic nature of data in the context of fit-for-purpose quality and the six V’s of big data.

KNMI brings a unique perspective exemplified by two use cases:

  • Weather data and its role in the energy transition and disaster risk reduction
  • Climate data and its role in the political arena

KNMI also keeps on expanding the number and type of data sources that it investigates for usability and veracity. Meta-data integrity and protocols are some of the crucial elements. In this talk we share our views, solutions and ongoing challenges around this topic with the audience.

Questions to the Panel of Speakers and Delegates move to the Seminar Rooms
Seminar Sessions
Networking Lunch Served in the Exhibition Area

Session TWO: Big Data, Big Impact – Making Data the Centrepiece of your Business

  • Manage and implement a secure and scalable Big Data architecture
  • Explore industry best requirements, ethics and governance mechanisms
  • Improve operational efficiencies and enhance long-term success of data initiatives
  • Cultural change and organisational adoption of data
Conference Chair’s Afternoon Address
What’s Missing from Big Data?

Satya Singh, Senior Product Manager, Expedia

Big data is a vague term – it is often mentioned at various places probably when someone has something to sell. There are a lot of small problems that usually occur in big data. Those problems become larger as we capture more and more. Today, we have an urge to keep collecting data. An urge to keep connecting various lines of evidence. A fundamentally flawed approach is to gather as much information as possible even if it can’t be quantified. Are we capturing a humungous amount of data to measure it qualitatively or are we acting on our emotional conviction? At what stage do we say that big data is too big to enable decisive action and how do we know what is missing from big data which can help us to arrive at decisions?

Ultimately, nobody wants data, we all want to make decisions which we can justify using data. None of the evidence suggests that data analysis is futile in fact it is profitable. However, profitability should not be confused with big data being correct or omniscient. Big data often excludes qualitative unbiased data which can be analysed to make decisions. Big data does an outstanding job regarding answering “What,” “Where” and “When” rather than “Who” and “why they do what they do.” This presentation explores what is missing from big data to make it truly ‘big.

Data as a Force for Good

Dr. Richard Benjamins, Group Chief Data Officer / Head of the Data Innovation Lab, AXA

This presentation explores the idea that data can be a force for good.

An Integrated Approach to Data Science

Robin Hagemans, Manager Data & Insights, Alliander

This presentation highlights how we need to change our approach to data programmes by considering and implementing data science at the beginning of operational projects.

How BI & Analytics is creating value for FrieslandCampina, 3 significant steps to make BI & Analytics successful

Aart Labee, Global Director BI & Analytics, FrieslandCampina

1.         Let’s start with a strategy!

2.         People and BI & Analytics

3.         Creating value by turning Data into Insight: challenges and lessons learned

Questions to the Panel of Speakers
Afternoon Networking and Refreshments served in the Exhibition Area
Creating and Managing a Data Analytics Team

Burce Gültekin, Head of Data Analytics Hub, NN Group

In five years, data scientists and analysts have gone from relative obscurity to an essential component of the decision-making process in large enterprises. They have transformed how businesses view their own systems and how they analyse their customer base.

But creating a viable team that produces powerful insights is not an easy task. How can your organisation create an analytics culture that encourages IT teams to enhance key processes? How can you encourage a culture of exploration, enquiry and innovation for all employees? This presentation will look at:

  • Finding the right talent for your organisation’s needs, and overcoming scarcity of talent
  • Skills needed for Big Data – what are the key disciplines required? And which skills are the hardest to source and develop?
  • The difficulties of deploying a data analytics team in a large enterprise
    Having a clear data strategy and ensuring your team can access the most important data
AkzoNobel Applies Predictive Analytics: Adding New Value to Support Decision Making Processes

Pascha Iljin, Manager FP&A Predictive Analytics and Big Data, AkzoNobel

One of Group Financial Planning and Analysis’ roles at AkzoNobel is controlling the processes of planning, budgeting, forecasting, and reporting. By applying Predictive Analytics to these processes, a new layer of value has been created. Now, forecasting models are being used using internal and external information to provide business with an even better understanding of what drives financial performance, and what future scenarios might look like.

Closing Keynote Address: Netherlands Red Cross

Stefania Giodini, Team Leader, 510 Global, Netherlands Red Cross

Questions to the Panel of Speakers
Closing Remarks from the Conference Chair
Conference Closes

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