2015 Big Data Week: Introducing the Speakers and Discussion Agendas

The theme of Big Data Week 2015 is “Big Data in Use”. How are retailers, publishers, advertisers, gamers, and others using big data in the real world? Numerous speakers in varying fields of expertise are joining in the discussion. Here are the speakers and discussion topics you can look forward to.

Kenneth Cukier – The Economist – The New Ethics of Big Data

Should the discussion of big data ethics shift from “How do we maintain individual privacy?” to “How can we make data more readily available?”

Most of the moral and ethical discussion surrounding big data to date has concerned privacy. However, big data has a lot to offer the world, including advancements in healthcare, humanitarian crises, science, and more. Cukier discusses a more sensible balance of privacy and public sharing in the arena of big data.

Andy Cotgreave – Tableau – You’ve Got Your Insight Data, Now What?

Trying to gain insight through the manipulation of data is not new; people have done it throughout history. The only difference today is in the type and volumes of data. Deriving insight is the same. Cotgreave discusses the solution to deriving insight from big data in this discussion.

Jane Zavalishina – Yandex Data Factory – How Machine Learning Disrupts Traditional Industries

Are robots going to take over all the jobs and leave humans without? This discussion by Zavalishina explains how machine learning will be applied in the areas of retail, advertising, and gaming, and what data analytics will be required to make it happen.

Mickael Ridley & Nick Henthorn – Telefonica Big Data & Exterion – Creating Value From Mobile Phone Data, Case Study in the OOH Market

In this presentation, Mickael and Nick will use an actual case study to demonstrate how Telefonica’s mobile phone data can be used to derive insights, specifically how Exterion Media intend to tailor advertising campaigns based on unique audience insights, changing the way that OOH advertising is bought, sold and optimized.

Panel – How to Become Data Driven – Alpesh Doshi

What should the strategies of a data-driven organization look like? This panel discussion explores how the organization’s functions should be organized in order to run big data projects efficiently and to the maximum potential.

John Abbey – Dunnhumby – Why Your Data Asset is Your Gold Mine

How big data can change the business is still not set in stone. This presentation discusses merging the online and offline worlds of retail, the Internet of Things, and more potential uses for big data in the years to come. Abbey also explains how to focus on your data asset strategy and what you should plan to own versus lease.

Chandan Rajan – Shop Direct – Business Change Through Predictive Analytics

Should companies invest in predictive analytics? A journey through how some companies extracted value from predictive analytics. The pros, cons and impact that could be expected from predictive and prescriptive analytics.

Should companies invest in predictive analytics? A journey through how some companies extracted value from predictive analytics. The pros, cons and impact that could be expected from predictive and prescriptive analytics.

Simon Monk – Start Small, Plan Big – Honest Caffe Story

Honest Café, an unmanned caffé chain, is a perfect example of how young new businesses are leveraging predictive analytics for the first time to make better, more strategic business decisions. Their first café went live 1 year ago and they are already operating across 6 more sites. Simon will go into detail, explaining how they have started small, but are planning big. Simon will go into detail, explaining how they have started small, but are planning big.

Panel – Get Organized for Big Data – The ASI – Dr. Marc Warner

This panel discussion will revolve around how to get organized for taking on big data.

Peter Bjørn Larsen – Hitachi Consulting – City Data Exchange – a Marketplace for Public and Private Data

This presentation will discuss the City Data Exchange, a commercial marketplace for selling and buying data in Copenhagen and the surrounding region. This is done in a co-creation process with the City of Copenhagen, the Capital Region and the national clean-tech cluster CLEAN, who initiated an innovative tender process with a competitive dialogue for the development of a data marketplace. An important part of the solution is to identify and engage the Big Data eco-system – the potential suppliers and consumers of data from both the public and private sector.

Neil Avery – Excelian – Evolving Patterns of Big Data

Utilizing tools like Docker, Ansible and Vagrant vendors are turning to open-source communities to drive big-data to become a low-friction, commodities solution in many industries. This talk explores these patterns and use cases and theorizes about where big data is headed. Data-Lakes, Enterprise Caches, Actors and other Lambda based patterns provide an exciting backdrop to the near future of big data patterns in many industries.

Charles Cai –  Making Sense of IoT Data

The IoT equals Big Data! In this talk we are going to discuss the latest development in Big Data, Machine Learning and Data Science, and use real IoT use cases to cover lifecycle of IoT data analytics: capturing, storing, cleaning, analyzing, predicting, maintaining, etc.

Martin Goodson – Skimlinks – From Wheelbarrows to Macbeth – Behavior Modeling for Publishers

Publishers’ content can be a rich source of data on users’ interests, brand affinity and purchase intent. When users interact with articles about products and brands, they generate click, page impression and conversion data. Analyzed correctly, such behavioral signals can help us to predict their future shopping behavior. The presentation will go through – possibly surprising – patterns of behavior, which can improve advertising campaign performance and personalize publishers’ content.

Matthew Doubleday – Shop Direct – Data Science in Retail

A list of potential applications of data mining or data algorithms will be presented, deep diving into at least one area to investigate both how the use case could be approached via a variety of algorithmic or machine learning techniques, and the logistical challenges that may apply to getting the solution live.

Alex Bordei – Bigstep – Data Lake and the Rise of the Microservices

What does the data lake have to offer your organization?

A Data Lake is more of a concept than a technology. It starts from the idea that having data of various types and formats in one place (especially unstructured data from an entire organization) allows correlations across data sources. Those correlations generate insight, which might not be visible from a single source. At its core, it is a storage strategy designed to support the new big data oriented analytics. Used wisely, it can help businesses make more informed decisions and also help build smarter automated processes that increase efficiency or improve customer experience.

In this talk we’ll give answers to the following questions:

1. Why should you start looking into a Data Lake?
2. Is it hard to build a Data Lake?
3. What are the main features that a Data Lake should bring in?
4. What’s the role of the microservices in the big data world?

You can see the agenda here.

Make sure you’ve got your ticket!