Strata in London 2013 Schedule

Below are the confirmed and scheduled talks at Strata in London 2013 (schedule subject to change).

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Create your own Strata schedule using the personal scheduler function. Mark the sessions, keynotes, and events you want to attend by selecting the calendar icon [calendar icon] next to each listing. Then go to your personal schedule and get your own customized schedule generated.

King's Suite - Balmoral
Add Automated Decision Making Online to your personal schedule
13:15 Automated Decision Making Online Noel Welsh (Underscore Consulting)
Add How to do Predictive Analytics with Limited Data to your personal schedule
14:05 How to do Predictive Analytics with Limited Data Ulrich Rueckert (Datameer)
Add The physics approach to big data to your personal schedule
17:15 The physics approach to big data Adam Kocoloski (Cloudant)
17:55 Plenary
Room: King's Suite - Balmoral
TBC
King's Suite - Sandringham
Add Running Non-MapReduce Big Data applications on Apache Hadoop to your personal schedule
13:15 Running Non-MapReduce Big Data applications on Apache Hadoop Hitesh Shah (Hortonworks), Siddharth Seth (Hortonworks)
Add Predictive Analytics with Hadoop to your personal schedule
14:05 Predictive Analytics with Hadoop Tomer Shiran (Dremio)
Add Putting the Sting in Hive to your personal schedule
15:35 Putting the Sting in Hive Alan Gates (Hortonworks)
Palace Suite - Buckingham Room
Add Dodging the Digital Creep Factor to your personal schedule
11:20 Dodging the Digital Creep Factor Shelley Evenson (Fjord)
Add Using Data For EVIL to your personal schedule
13:15 Using Data For EVIL Francine Bennett (Mastodon C), Duncan Ross (TES Global)
Add Digital analytics & privacy: it's not the end of the world to your personal schedule
14:05 Digital analytics & privacy: it's not the end of the world Aurélie Pols (Mind Your Privacy)
Add Information Revolution in Government to your personal schedule
16:25 Information Revolution in Government James Stewart (jystewart.net), James Abley (Government Digital Service)
Add Big Data as a Source for Official Statistics to your personal schedule
17:15 Big Data as a Source for Official Statistics Piet Daas (Statistics Netherlands), Edwin De Jonge (Statistics Netherlands)
Add Data Science London Meetup (Community Event) to your personal schedule
18:30 Plenary
Room: Palace Suite - Buckingham Room
Data Science London Meetup (Community Event)
Palace Suite - Blenheim Room
Add Lean Analytics: Using data to build a better business faster to your personal schedule
11:20 Lean Analytics: Using data to build a better business faster Alistair Croll (Solve For Interesting)
Add SapientNitro Mobile Commerce Case Study: Using big data to understand the mobile in-store shopping experience to your personal schedule
16:25 SapientNitro Mobile Commerce Case Study: Using big data to understand the mobile in-store shopping experience Sheldon Monteiro (SapientNitro), John Cain (SapientNitro), Thomas John Mcleish (SapientNitro)
Add The Intersection of Data and Anthropology to your personal schedule
17:15 The Intersection of Data and Anthropology Roger Magoulas (O'Reilly Media)
Westminster
Add Capturing value from Big Financial Data to your personal schedule
11:20 Capturing value from Big Financial Data Marco Bressan (BBVA), Carme Artigas (Synergic Partners)
Add Hadoop Beyond Batch: Real-time Workloads, SQL-on-Hadoop, and the Virtual EDW to your personal schedule
13:15 Hadoop Beyond Batch: Real-time Workloads, SQL-on-Hadoop, and the Virtual EDW Marcel Kornacker (Cloudera), Robin Stephenson (Mendeley Ltd)
Add Using Social Analytics for Insight to your personal schedule
14:05 Using Social Analytics for Insight Andy Cotgreave (Tableau)
Add Welcome to your personal schedule
9:00 Plenary
Room: King's Suite
Welcome Edd Wilder-James (Silicon Valley Data Science), Kaitlin Thaney (Mozilla Science Lab)
Add Startup Showcase Winners Annouced to your personal schedule
9:10 Plenary
Room: King's Suite
Startup Showcase Winners Annouced
Add Perception is Key: Telescopes, Microscopes and Data to your personal schedule
9:15 Plenary
Room: King's Suite
Perception is Key: Telescopes, Microscopes and Data Mark Madsen (Third Nature)
Add Gavin Starks to your personal schedule
9:35 Plenary
Room: King's Suite
Gavin Starks Gavin Starks (Open Data Institute)
Add Bridges in the Ocean — Storytelling in the Age of Big Data to your personal schedule
9:55 Plenary
Room: King's Suite
Bridges in the Ocean — Storytelling in the Age of Big Data Julie Steele (Silicon Valley Data Science)
Add The Future Isn't What it Used to Be to your personal schedule
10:15 Plenary
Room: King's Suite
The Future Isn't What it Used to Be James Burke
Add Ignite Strata + Velocity to your personal schedule
18:30 Plenary
Room: King's Suite
Ignite Strata + Velocity Nicola Hughes (ThoughtWorks), Duncan Ross (TES Global)
10:50 Morning Break
Room: Monarch Suite
Add Tuesday Lunch / Birds of a Feather Discussions to your personal schedule
12:00 Lunch
Room: Monarch Suite
Tuesday Lunch / Birds of a Feather Discussions
14:45 Afternoon Break
Room: Monarch Suite
8:00 Morning Coffee Service
Room: King's Suite Foyer
11:20-12:00 (40m) Data Science
Scaling by Cheating: Approximation, Sampling and Fault-friendliness for Scalable Big Learning
Sean Owen (Cloudera)
To keep analyzing more data, and faster, we need a secret weapon: cheating. In this brief survey, learn how you may be doing too much work in your analytics and learning processes, and how giving up a little accuracy can gain a lot of performance. With examples from Apache Hadoop, Mahout, and ML tools from Cloudera.
13:15-13:55 (40m) Data Science
Automated Decision Making Online
Noel Welsh (Underscore Consulting)
Analytics is useless if it doesn't lead to action. It is often desirable to put a computer in control of decision making. In this talk I'll discuss bandit algorithms, a class of decision making algorithms that solve a simple but widely applicable decision problem, and have found application in ad serving, content recommendation, and more.
14:05-14:45 (40m) Data Science
How to do Predictive Analytics with Limited Data
Ulrich Rueckert (Datameer)
Even if one has big data, sometimes there is a lack of key data. This is a problem for predictive analytics: if there is only a limited amount of training material (e.g. user ratings, categorized documents), then it is hard to generate accurate models. The talk introduces new semi-supervised learning methods to overcome this problem by utilizing the vast amount of unlabeled data.
15:35-16:15 (40m) Data Science
Dealing with Uncertainty: What the reverend Bayes can teach us.
Jurgen Van Gael (Rangespan, Ltd)
As data scientists, uncertainty is all around us: data is noisy, missing, wrong or inherently uncertain. In this talk I want to introduce a branch of statistics called Bayesian reasoning which is a unifying, consistent, logical and practically successful way of handling uncertainty. In short, I'd like to convince people that Bayes rule is the E=MC^2 of data science.
16:25-17:05 (40m) Data Science
Probabalistic Data Matching – How mathematics helps find duplicates in data
Stefan Franczuk (Cognizant)
How do you indentify duplicate data and why is it important? What do you do with such data when you find it? Data Matching using the mathematics of probability has been around since the 1950’s. But, how does it actually work? What is the mathematics behind it? How do probabilities allow us to identify duplicate entries?
17:15-17:55 (40m) Data Science
The physics approach to big data
Adam Kocoloski (Cloudant)
This talk will discuss how particle physics research can inform the field of data science. The importance of blind analyses and machine learning algorithms will be discussed as tools for filtering growing bodies of data as the big data trend continues.
17:55-18:30 (35m)
Plenary
To be confirmed
11:20-12:00 (40m) Tools & Technology
Taming the ETL beast – How LinkedIn uses metadata to reliably run complex ETL flows
Rajappa Iyer (LinkedIn)
To feed LinkedIn's data-driven products, we need to run a complex graph of ETL workflows that deliver the right data to the right systems reliably on a 24x7 basis. To achieve this goal, we have developed a metadata system that captures process dependencies, data dependencies, and execution histories -- this system also lays the foundation for a combined dataflow and workflow engine.
13:15-13:55 (40m) Data Science
Running Non-MapReduce Big Data applications on Apache Hadoop
Hitesh Shah (Hortonworks), Siddharth Seth (Hortonworks)
Apache Hadoop has become popular from its specialization in the execution of MapReduce programs. However, it has been hard to leverage existing Hadoop infrastructure for various other processing paradigms such as real-time streaming, graph processing and message-passing. That was true until the introduction of Apache Hadoop YARN in Apache Hadoop 2.0.
14:05-14:45 (40m) Data Science, Tools & Technology
Predictive Analytics with Hadoop
Tomer Shiran (Dremio)
Predictive Analytics has emerged as one of the primary use cases for Hadoop, leveraging various Machine Learning techniques to increase revenue or reduce costs. In this talk we provide real-world use cases from several different industries, and then discuss the open source technologies available to companies wishing to implement Predictive Analytics with Hadoop.
15:35-16:15 (40m) Tools & Technology
Putting the Sting in Hive
Alan Gates (Hortonworks)
People want more out of Hive. They want it to be fast, useful, and connect to their tools. Work is being done to reduce start up time, improve the optimizer, extend it to use Tez, process records 50x faster, add support for functions like RANK, add subqueries, and add standard SQL datatypes. We will review this work plus show current benchmarks.
16:25-17:05 (40m) Tools & Technology
Mixing low latency with analytical workloads for Customer Experience Management
Neil Ferguson (NICE Systems)
NICE Systems is a leading provider of Customer Experience Management software, providing real-time offer management and predictive analytics applications based on HBase. We have recently migrated to HBase from our own custom-built data store, and in this session we will share the challenges we overcame getting HBase to perform to our demanding performance requirements.
17:15-17:55 (40m) Data Science, Tools & Technology
Customer Behaviour Analytics: Billions of Events to one Customer-Product Property Graph
Paul Lam (uSwitch)
What questions would you ask if you have a Facebook-like graph of what your customer likes, what they bought, and what they viewed? This is what we built at uSwitch by transforming flat data from Hadoop into Neo4J. This talk will walk through how we bridged big data and linked data technologies and the results of such amalgamation.
11:20-12:00 (40m) Design
Dodging the Digital Creep Factor
Shelley Evenson (Fjord)
This session will cover the rapidly changing way that machines are taking on different parts of our lives, making decisions for us and altering our lives with our own data. Shelley Evenson will address how designers need to keep their human focus in order to truly capitalise on the benefits of big data without allowing technology to take over.
13:15-13:55 (40m) Data Science, Ethics, Policy & Privacy
Using Data For EVIL
Francine Bennett (Mastodon C), Duncan Ross (TES Global)
Being good is hard. Being evil is much more fun and gets you paid a lot more. We give a survey of the field of doing high-impact evil with data and analysis. We will look at some of the simplest things you can do to make the maximum (negative) impact on your friends, your business and the world. If you happen to learn something about doing good with data that will be your problem.
14:05-14:45 (40m) Data Science, Ethics, Policy & Privacy
Digital analytics & privacy: it's not the end of the world
Aurélie Pols (Mind Your Privacy)
Analytics best practices, data feeds and flows between tools and continents are put in parallel with legislation, showing which steps to undertake for legal compliance; how to train for data protection & assure minimal liability. It’s not about security, goes beyond the cookie debate, highlighting how the EU Personal Data Protection Regulation will influence analytics & how Privacy by Design helps
15:35-16:15 (40m) Business & Industry, Data Science, Tools & Technology
Interactive graphics in pharmaceutical R&D: The right decision
Francois Mercier (mgrafit)
To take the right decision, you need the right data. As complexity and abundance of data increase, the communication of data analysis results becomes more challenging. Grounding our talk in the pharma R&D arena, we illustrate how animated and interactive graphics can streamline communication on complex data analysis and inform decision making.
16:25-17:05 (40m) Data Science, Design, Open Data
Information Revolution in Government
James Stewart (jystewart.net), James Abley (Government Digital Service)
The UK Government team behind the GOV.UK website talk about their work on the Performance Platform, a suite of services and a cultural shift taking people away from immensely detailed value stream maps about a call-centre and paper process (which might be an inherently 5-day long journey), to something that's digital, lightweight, fast and pleasant to use.
17:15-17:55 (40m) Data Science
Big Data as a Source for Official Statistics
Piet Daas (Statistics Netherlands), Edwin De Jonge (Statistics Netherlands)
Big Data are very interesting for official statistics. Results obtained by analyzing large amounts of Dutch traffic loop detection records, Mobile phone data and Dutch social media messages are discussed to illustrate this.
18:30-20:30 (2h)
Data Science London Meetup (Community Event)
Data Science London will host their meetup at Strata Conference London on 12 November.
11:20-12:00 (40m) Business & Industry
Lean Analytics: Using data to build a better business faster
Alistair Croll (Solve For Interesting)
The Lean Startup model showed a generation of founders how to launch companies smarter and faster. At the core of this model is a constant cycle of building, measuring, and learning. In this session, we'll look at the "measure" part of this cycle, and how organizations of all sizes can use data to build a better business faster.
13:15-13:55 (40m) Business & Industry
Giving organisations new capabilities to ask the right business questions
Stephen Simpson (Independent)
Making data work requires that organisations define success for their company, provide clear business goals, & articulate the right business questions. The best approach to overcoming the cognitive pitfalls that lead to failing to ask the right question come from the intelligence services. This seminar outlines what they do, and suggests how to use it effectively inside a typical business.
14:05-14:45 (40m) Business & Industry
Turning the oil tanker: Making data work in a large organisation
Duncan Bloor (BBC)
Some big organisations love the idea of using data to inform decision making but find the reality a little daunting to say the least. How are we demystifying data in the BBC and overcoming editorial fears about it lessening the view of the trusted human in making content decisions?
15:35-16:15 (40m) Business & Industry, Tools & Technology
Hadoop travels the world at 25 Billion GPS points a day in TomTom
Pascal Clarysse (TomTom)
Learn how hadoop is helping TomTom to make fresher maps by continuously processing the incoming GPS data and how hbase is used to present that data to an Operator
16:25-17:05 (40m) Business & Industry, Data Science, Tools & Technology
SapientNitro Mobile Commerce Case Study: Using big data to understand the mobile in-store shopping experience
Sheldon Monteiro (SapientNitro), John Cain (SapientNitro), Thomas John Mcleish (SapientNitro)
78% of consumers use their smartphone while shopping in-store. What are they doing? More importantly, why? For all the media buzz around showrooming – look in-store, buy online - there is little insight on the issue. SapientNitro explains how key business questions drove hypotheses, data collection using novel instruments, and insights from analytic tools for testing and interpretive analysis.
17:15-17:55 (40m) Data Science
The Intersection of Data and Anthropology
Roger Magoulas (O'Reilly Media)
How combining quantitative data analysis and qualitative social science work can complement each other, providing deeper understanding of behavior and open new doors of enquiry.
11:20-12:00 (40m) Sponsored
Capturing value from Big Financial Data
Marco Bressan (BBVA), Carme Artigas (Synergic Partners)
The large-scale deployment of a big data strategy in the retail financial services sector poses specific challenges in terms of infrastructure, data limitations, organizational structure and portfolio definition and execution. We will share how we are addressing these challenges as well as selected demos and solutions, with focus on promising new financial product lines enabled by big data.
13:15-13:55 (40m) Sponsored
Hadoop Beyond Batch: Real-time Workloads, SQL-on-Hadoop, and the Virtual EDW
Marcel Kornacker (Cloudera), Robin Stephenson (Mendeley Ltd)
Attendees will leave this session with a deeper understanding of how organizations are using Hadoop to solve real business problems today, and how recent advancements in the Hadoop ecosystem are expanding the platform's capabilities to serve larger enterprise requirements for a virtual EDW.
14:05-14:45 (40m) Sponsored
Using Social Analytics for Insight
Andy Cotgreave (Tableau)
How can companies use social and business data together to gain insight? See how Tableau's native Google BigQuery connector links seamlessly to live data in BigQuery and creates interactive visualizations without writing a single line of code. Find out how to share your results on the web and mobile in minutes.
9:00-9:10 (10m)
Welcome
Edd Wilder-James (Silicon Valley Data Science), Kaitlin Thaney (Mozilla Science Lab)
Program Chairs, Edd Dumbill and Kaitlin Thaney, open the second day of keynotes.
9:10-9:15 (5m)
Startup Showcase Winners Annouced
Winners of the Startup Showcase are announced.
9:15-9:35 (20m)
Perception is Key: Telescopes, Microscopes and Data
Mark Madsen (Third Nature)
We hear stories of how big data is unprecedented and about the latest disruptive products to hit the market, products that are totally different and will change everything. Yet looking at the underlying concepts, most of these aren’t all that new and the ones that are new are being explained in the terms of the old, in the same way cars were described as “horseless carriages.”
9:35-9:55 (20m)
Gavin Starks
Gavin Starks (Open Data Institute)
Gavin Starks, CEO, Open Data Institute (ODI).
9:55-10:15 (20m) Data Science
Bridges in the Ocean — Storytelling in the Age of Big Data
Julie Steele (Silicon Valley Data Science)
Data science may seem like a revolutionary new field, but it is merely the latest incarnation of a tradition as old as we are: storytelling. And because it is part of such an inherently human practice, it is most valuable when it takes humanity into account. This talk explores how to use data and the techniques associated with data to build things that matter, by looking back to look forward.
10:15-10:50 (35m) Data Science
The Future Isn't What it Used to Be
James Burke
Keynote by James Burke, science and technology historian, futurist, and author.
18:30-19:30 (1h)
Ignite Strata + Velocity
Nicola Hughes (ThoughtWorks), Duncan Ross (TES Global)
If you had five minutes on stage what would you say? What if you only got 20 slides and they rotated automatically after 5 seconds? We’ll find out again this year, the second day of Strata in London and the day before Velocity Europe—for one big, combined, rip-roaring Ignite event.
10:50-11:20 (30m)
Break: Morning Break
12:00-13:15 (1h 15m)
Tuesday Lunch / Birds of a Feather Discussions
Lunch and Birds of a Feather (BoF) Discussions
14:45-15:35 (50m)
Break: Afternoon Break
8:00-9:00 (1h)
Break: Morning Coffee Service

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