Presented By O'Reilly and Cloudera
Make Data Work
5–7 May, 2015 • London, UK
 

Strata + Hadoop World in London 2015 Schedule

Use the calendar icon [calendar icon] next to each listing you want to attend. Then use the personal schedule button below to generate your schedule.

Wednesday, 6 May

King's Suite - Balmoral
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10:55 Ideas that Matter Tim Harford (The Financial Times)
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13:45 Deploying machine learning in production Alice Zheng (Amazon)
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14:35 What's there to know about A/B testing? Noel Welsh (Underscore Consulting)
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16:15 Forecasting space-time events Jeremy Heffner (Azavea)
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17:05 Deep learning made doubly easy with reusable deep features Carlos Guestrin (Apple | University of Washington )
King's Suite - Sandringham
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11:45 Scale out databases for CERN use cases Zbigniew Baranowski (CERN)
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13:45 Apache Kylin - Extreme OLAP engine for Hadoop Luke Han (Kyligence Inc), Yang Li (eBay)
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14:35 Scaling SQL-on-Hadoop for BI Yanpei Chen (Cloudera), Dileep Kumar (Cloudera Inc)
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17:05 Leading change in data engineering Neil Martin (comparethemarket.com)
Buckingham Room - Palace Suite
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10:55 Apache Spark: The faster new execution engine for Apache Hive Xuefu Zhang (Cloudera), Rui Li (Intel)
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11:45 Apache Spark: What's new; what's coming Patrick Wendell (Databricks)
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13:45 Systems that enable data agility: Lessons from LinkedIn Martin Kleppmann (University of Cambridge)
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14:35 Using the Zeta Architecture: To become a hero Jim Scott (MapR Technologies)
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16:15 From Bigtable to HBase and back again - history and future Cory O'Connor (Google), Emre Baran (Qubit)
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17:05 Big JSON, baffling performance Jacques Nadeau (Dremio)
Blenheim Room - Palace Suite
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13:45 Bridging big data with big health Leslie McIntosh (Washington University School of Medicine)
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14:35 How big data is redefining banking Ankit Tharwani (Barclays UK), Aengus Rooney (Barclays)
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17:05 Data-driven retailing in the modern world Jason Foster (Marks and Spencer)
St. James / Regents
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10:55 The Internet of trains Gerhard Kress (Siemens AG)
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14:35 How to talk to a house Simon Elliston Ball (Hortonworks)
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17:05 Smart cars of tomorrow: real-time driving patterns Ellie Dobson (Pivotal), Michael Minella (Pivotal), Ronert Obst (Pivotal)
Windsor Suite
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10:55 Modernize Your Data Management by Optimizing Your Data Warehousing Environments Paul Davies (Cisco), Dimitris Papavassiliou (Cisco)
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14:35 Purpose Built Analytics Infrastructure, Intel and HP Powering Performance at Scale Brandon Draeger (Intel), Joseph George (Hewlett-Packard (HP))
Westminster Suite
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14:35 Hadoop Application Architectures - ask us anything Mark Grover (Lyft), Jonathan Seidman (Cloudera), Gwen Shapira (Confluent), Ted Malaska (Blizzard Entertainment)
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16:15 Practical machine learning - ask us anything Angie Ma (ASI), Anjali Samani (ASI), Marc Warner (ASI), Ken Williams (The ASI)
Hilton Meeting Room 1-3
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9:00 Apache Spark advanced training (Day 2) Olivier Girardot (Lateral Thoughts), Sameer Farooqui (Databricks)
Hilton Meeting Room 4-6
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9:00 Practical machine learning (Day 1) Angie Ma (ASI), Marc Warner (ASI), Andrew Brookes (ASI Data Science), Anjali Samani (ASI), Alessandra Staglianò (The ASI), Ken Williams (The ASI), Mahesan Niranjan (University of Southampton), Elena Chatzimichali (Wellcome Trust Sanger Institute, Cambridge)
8:00 Coffee Break sponsored by HGST
Room: King's Suite
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9:00 Plenary
Room: King's Suite
Wednesday Keynote Welcome Roger Magoulas (O'Reilly Media), Doug Cutting (Cloudera), Alistair Croll (Solve For Interesting)
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9:10 Plenary
Room: King's Suite
The data adventure in Santander Maite Agujetsas (Santander Group)
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9:25 Plenary
Room: King's Suite
Hadoop 2015: What we’ve learned in 5 years Rick Farnell (Think Big, A Teradata Company)
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9:35 Plenary
Room: King's Suite
Keynote with Cait O'Riordan Cait O'Riordan (Shazam)
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9:45 Plenary
Room: King's Suite
Hadoop and healthcare David Richards (WANdisco)
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9:50 Plenary
Room: King's Suite
Bigtable’s next big step Cory O'Connor (Google)
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9:55 Plenary
Room: King's Suite
Keynote with Julie Meyer Julie Meyer (Ariadne Capital)
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10:05 Plenary
Room: King's Suite
Ideas that Matter Tim Harford (The Financial Times)
10:25 Morning break sponsored by WANdisco
Room: Monarch Suite
15:15 Afternoon break sponsored by Google
Room: Monarch Suite
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17:45 Plenary
Room: Monarch Suite
Attendee Reception
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12:25 Lunch sponsored by Teradata
Room: Sponsor Pavilion / Westminster Suite / Fiamma Restaurant
Wednesday Lunchtime BoF Tables (located in the Monarch Suite)
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19:15 Plenary
Room: Offsite
Data After Dark: Pub Crawl
18:45 Dinner
Room: On Your Own
10:55-11:35 (40m) Data Science
Ideas that Matter
Tim Harford (The Financial Times)
We're always talking about "innovation", but - says Tim Harford - there are really two very different kinds of innovation. Using stories from sport, science, music and military history, Tim will make you think different about where good ideas come from and how they should be encouraged.
11:45-12:25 (40m) Data Science
Improving feature engineering in the lab and production with Ivory
Ben Lever (Ambiata)
Ivory is a new open-source, Hadoop-based data store that focuses on changing the way we approach the critical and time-consuming activity of scalable feature engineering. It both simplifies and adds rigour to data science pipelines, aiding in their transition from the lab to production environments.
13:45-14:05 (20m) Data Science
Deploying machine learning in production
Alice Zheng (Amazon)
Building and deploying predictive applications require knowing how to evaluate, test, and track the performance of machine learning models over time. Using available off-the-shelf tools, this talk engages potential application builders on topics such as common evaluation metrics, A/B testing set up, tracking model performance, tracking usage via real-time feedback, and updating models.
14:05-14:25 (20m) Data Science
What we are made of: Analyzing the human genome with SQL
Felipe Hoffa (Google)
How big is the human genome? What tools can we use to manage and understand it? Turns out the same tools used for traditional purposes (Hadoop, Spark, BigQuery, Dataflow, and SQL) can be applied to genomics. In this session we'll introduce the basics of managing genomes with our favorite big data tools, and draw parallels with more traditional use cases like analyzing view logs.
14:35-14:55 (20m) Data Science
What's there to know about A/B testing?
Noel Welsh (Underscore Consulting)
A/B testing is easy; it's just an application of hypothesis testing, taught in every first year stats course. My goal in this talk is to convince you that this view is wrong. There is a lot of subtlety in creating a meaningful test, and this subtlety is important in practice. I'll cover issues from methodology to epistemology, giving insights and tools directly applicable to practice.
14:55-15:15 (20m) Data Science
Measuring the benefit effect for customers with Bayesian predictive modeling
JeongMin Kwon (-)
Offering benefits is a classic and important strategy for acquisition of new customers and churn management. For measuring benefits with data, this model combines multivariate testing like A/B testing and Bayesian time series prediction modeling. The model is implemented in an R and CausalImpact package. This presentation will demonstrate the model structure and provide a case study.
16:15-16:55 (40m) Data Science
Forecasting space-time events
Jeremy Heffner (Azavea)
We often face the need to analyze the count of discrete events which occur at a specific time and place, whether they are crime events, taxi requests, or phone calls. Forecasting these space-time events brings particular challenges: finding suitable tools for geographic processing, and techniques for modeling the data. The session will cover the lessons learned in building such a system.
17:05-17:45 (40m) Data Science
Deep learning made doubly easy with reusable deep features
Carlos Guestrin (Apple | University of Washington )
Deep learning is a promising machine learning technique with a high barrier to entry. In this talk, we provide an easy entry into this field via "deep features" from pre-trained models. These features can be trained on one data set for one task and used to obtain good predictions on a different task, on a different data set. No prior experience is necessary.
10:55-11:35 (40m) Hadoop Platform
Friction-free ETL: Automating data transformation with Impala
Marcel Kornacker (Cloudera)
In this talk, attendees will learn about Impala’s approach to on-the-fly, automatic data transformation, which in conjunction with the ability to handle nested structures such as JSON and XML documents, addresses the needs of at-source analytics — including direct querying of your input schema, immediate querying of data as it lands in HDFS, and high performance on par with specialized engines.
11:45-12:25 (40m) Hadoop Platform
Scale out databases for CERN use cases
Zbigniew Baranowski (CERN)
Cloudera Impala can be considered as an alternative solution to a relational database for data warehouse-like workloads. The CERN database community did a close evaluation of the Impala engine in respect to CERN's needs. In this presentation we will discuss our experience with the technology, and will report on a queries performance in comparison to data access using an Oracle RDBMS.
13:45-14:25 (40m) Hadoop Platform
Apache Kylin - Extreme OLAP engine for Hadoop
Luke Han (Kyligence Inc), Yang Li (eBay)
Apache Kylin is an open source distributed analytics engine contributed by eBay Inc. that provides SQL interface and multi-dimensional analysis (OLAP) on Hadoop, supporting extremely large datasets. It was accepted as an Apache Incubator Project on Nov 25, 2014. Website: http://kylin.io
14:35-15:15 (40m) Hadoop Platform
Scaling SQL-on-Hadoop for BI
Yanpei Chen (Cloudera), Dileep Kumar (Cloudera Inc)
SQL-on-Hadoop systems that support business intelligence (BI) use cases must handle hundreds or even thousands of concurrent users. We will talk about how to scale your SQL-on-Hadoop system to a large number of concurrent users, and how to verify that your system can support BI.
16:15-16:55 (40m) Hadoop Platform
The year in review - key changes in the Hadoop platform in the past 12 months
Jairam Ranganathan (Cloudera)
With hundreds of developers from a variety of organizations participating, Hadoop moves quickly. This talk will survey the important changes admins and users should be aware of and their impacts on various use cases.
17:05-17:45 (40m) Hadoop Platform
Leading change in data engineering
Neil Martin (comparethemarket.com)
Compare the Market’s senior project manager Neil Martin will present the lessons learned whilst delivering a successful yet complex multifaceted project to reinvigorate the organization’s data infrastructure.
10:55-11:35 (40m) Hadoop & Beyond
Apache Spark: The faster new execution engine for Apache Hive
Xuefu Zhang (Cloudera), Rui Li (Intel)
This presentation will talk about the motivation, design principles, architecture, challenges, and current status of the community project to make Spark a new back-end processing engine for Hive.
11:45-12:25 (40m) Hadoop & Beyond
Apache Spark: What's new; what's coming
Patrick Wendell (Databricks)
Apache Spark is a popular engine for fast and efficient data processing. This talk will cover recent feature additions to Spark, such as the elastic scaling support, new algorithms in MLlib, and the Spark SQL datasources API. It will also outline the Spark roadmap for upcoming months. Since this talk is not until May, specific roadmap details will be determined close to the talk itself.
13:45-14:25 (40m) Hadoop & Beyond
Systems that enable data agility: Lessons from LinkedIn
Martin Kleppmann (University of Cambridge)
Data is only useful if you can process it, analyse it, and create valuable products from it. If you have an idea for a new data-driven product, how long does it take you to get it into production? In this talk, we'll discuss Apache Kafka and Samza, open source tools created at LinkedIn with the goal of helping teams implement data products and ship them to production rapidly.
14:35-15:15 (40m) Hadoop & Beyond
Using the Zeta Architecture: To become a hero
Jim Scott (MapR Technologies)
The Zeta Architecture is the enterprise architecture that describes how to move your business to the next generation. It combines a data center-wide resource manager, a rock-solid distributed file system, containerization, a big data processing platform, stream processing, a real-time data store, independent application architectures, and custom enterprise applications.
16:15-16:55 (40m) Hadoop & Beyond
From Bigtable to HBase and back again - history and future
Cory O'Connor (Google), Emre Baran (Qubit)
This presentation will provide a brief technical overview of Google Bigtable and the global problems we solve internally at Google with this revolutionary architecture. We'll discuss some of our innovations since the original paper was released, what we’ve been working on with HBase, and include announcements on where we're headed next!
17:05-17:45 (40m) Hadoop & Beyond
Big JSON, baffling performance
Jacques Nadeau (Dremio)
Technical overview of how Apache Drill enables high performance analysis of complex and dynamic data. Will discuss the role of self-describing data in a modern distributed data lake, the requirement for adaptive execution, and how to expose dynamic schema using SQL.
10:55-11:35 (40m) Business & Industry
Where the rubber meets the road: Decision-making based on data
Christine Foster (ShopKeep)
How to make data and analytics valuable to a business. How to improve a business with data and analytics. I'm a business person first, and an analyst second. I have seen many excellent data scientists fail to implement their ideas. I have also seen many excellent business people fail to generate value from data.
11:45-12:25 (40m) Business & Industry
It ain’t what you do to data, it’s what you do with it
Edd Wilder-James (Google)
Creating value from data needs a new mindset. To fully exploit new big data tools and architectures, we need a new way of thinking: data as the raw material of growth. How do you share this understanding in your company, and how do you plan for success?
13:45-14:25 (40m) Business & Industry
Bridging big data with big health
Leslie McIntosh (Washington University School of Medicine)
Most health systems have been slow to embrace new techniques and technologies, despite the dire need to get more value from their data, more quickly. In this talk, I will discuss the state of health informatics; bringing new tools and processes to healthcare; navigating politics; and collaborating with industry and startups.
14:35-15:15 (40m) Business & Industry
How big data is redefining banking
Ankit Tharwani (Barclays UK), Aengus Rooney (Barclays)
At Barclays, we have succeeded in building initial info-led propositions based on the ability to analyze terabytes of data in seconds. We overcame the challenges of bringing together structured and unstructured data by employing innovative solutions.
16:15-16:55 (40m) Business & Industry
Automating decision-making with big data: How to make it work
Lars Trieloff (Blue Yonder)
While many companies are struggling to adopt big data and unlock its potential, facing challenges of visualization and democratization of insight, a number of industry leaders are leapfrogging big data adoption to circumvent the analyst bottleneck by going straight to automation of core business processes. This requires overcoming a set of tough cultural, technical, and scientific challenges.
17:05-17:45 (40m) Business & Industry
Data-driven retailing in the modern world
Jason Foster (Marks and Spencer)
This session will look at the journey Marks & Spencer have been on and have ahead in using data to help turn it from a traditional British high street retailer into a global, multi-channel retailer. It will explore the impact on culture, technology, ways of working, and capabilities needed to drive the change.
10:55-11:35 (40m) IoT/Machine Data
The Internet of trains
Gerhard Kress (Siemens AG)
Trains today are complex systems of many embedded subsystems. Market demands are changing and data analytics is now absolutely required to deliver market leading offerings to customers. What value is hidden in train data? We will discuss different approaches and explore opportunities to reduce the cost of rolling stock fleet maintenance, minimize train downtime and improve fleet availability.
11:45-12:25 (40m) IoT/Machine Data
Multi-model databases and the art of aircraft maintenance
Max Neunhöffer (ArangoDB)
We present a concrete case study of a situation where it was necessary to have different data models (documents and graphs) in the same database engine using a common query language. A single aircraft already contains some 6,000,000 parts, not counting components. Any single data model inevitably leads to inefficient queries, though queries are nevertheless crucial for the application.
13:45-14:05 (20m) IoT/Machine Data
The internet of everything: Creating programmable cities, cars, and homes
yodit stanton (opensensors.io)
Creating programmable cities, cars, and homes using sensors and data. Explore a number of IoT use cases and aims to give some practical implementation experience reports of building connected products in the context of cities, cars, and homes. We will also show what happens when you make it super-easy to plug sensor data into multiple systems, creating a new type of programmable world.
14:05-14:25 (20m) IoT/Machine Data
Turning streaming sushi into streaming data means happier customers
Adi Krishnan (Amazon Web Services)
In Japan, Kaiten (conveyer belt) sushi is a fast business. With 360 stores, SushiRo is one of the largest Kaiten operators in the world. Faced with 24-hour BI cycles and lost data due to daily batch reporting, SushiRo turned to AWS for streaming analytics. Learn how Amazon Kinesis and Redshift help SushiRo capture real-time data from Sushi plates and convert it into business insights.
14:35-15:15 (40m) IoT/Machine Data
How to talk to a house
Simon Elliston Ball (Hortonworks)
How do you negotiate with your house? This is a tale of home automation, machine learning, and a new way of programming. Find out how I used machine learning, micro-services and image recognition to light my house, mainly in the dark.
16:15-16:55 (40m) IoT/Machine Data
How (the Internet of) Things are turning the Internet upside down
Ted Dunning (MapR Technologies)
Just when we thought the last mile problem was solved, the Internet of Things is turning the last mile problem of the consumer Internet into the first mile problem of the industrial Internet. This inversion impacts every aspect of the design of networked applications. I will show how to use existing Hadoop ecosystem tools, such as Spark, Drill and others, to deal successfully with this inversion.
17:05-17:45 (40m) IoT/Machine Data
Smart cars of tomorrow: real-time driving patterns
Ellie Dobson (Pivotal), Michael Minella (Pivotal), Ronert Obst (Pivotal)
Intelligent prediction of driving behavior has a wide range of applications. For this session, we will explore a connected car. We will cover the architecture used for streaming real-time sensor data from a car, and the machine learning techniques utilized to predict route and range. Coming out of this session, you’ll understand how open source technologies can serve as a platform for the IoT.
10:55-11:35 (40m) Sponsored
Modernize Your Data Management by Optimizing Your Data Warehousing Environments
Paul Davies (Cisco), Dimitris Papavassiliou (Cisco)
This session will look at Cisco’s Data Warehouse Optimisation (DWO) Solution, and explores how it reduces ever-growing data warehouse management costs, whilst delivering a greater variety and volume of data that can can be ingested and stored to derive new business insights.
11:45-12:25 (40m) Sponsored
Lowering the entry point to getting going with Hadoop and obtaining business value
Mark Torr (SAS)
This presentation shares how SAS can help spread the use of Hadoop to less technical audiences, showcasing some of the end-user technologies already implemented at SAS customers that can help across the spectrum of data ingestion and management, visualization, and analytics.
13:45-14:25 (40m) Sponsored
No more standby read-only Hadoop disaster recovery sites
Brett Rudenstein (WANdisco)
This session will describe a method of data replication between Hadoop in multiple locations that achieves 100% utilization of globally-distributed infrastructure, while maintaining data consistency in the face of network, process, and machine failures. The session will also describe how computation is executed across sites, and provide example architectures using MapReduce and Hive.
14:35-15:15 (40m) Sponsored
Purpose Built Analytics Infrastructure, Intel and HP Powering Performance at Scale
Brandon Draeger (Intel), Joseph George (Hewlett-Packard (HP))
Join Intel and HP as they discuss new innovations in new server designs powered by Intel Architecture that are enabling customers to adopt and grow their big data environments with confidence.
16:15-16:55 (40m) Sponsored
Oozie or easy: Managing Hadoop workflows the EASY way
Tom Geva (BMC Software)
As Hadoop adoption continues to grow, the number of workflows and their complexity increases. This session describes how organizations are managing Hadoop and big data workflows with an enterprise workflow solution that provides a graphical user interface for managing all of the complex components of the enterprise application fabric.
17:05-17:45 (40m) Sponsored
How being an information generation is driving Big Data and business change
Mark Sear (EMC)
Big data. Is this the real life? Is this just fantasy? Caught in a landslide. No escape from reality. A brief walk through some of the developments that are happening now with Big Data at the core.
14:35-15:15 (40m) Ask Us Anything
Hadoop Application Architectures - ask us anything
Mark Grover (Lyft), Jonathan Seidman (Cloudera), Gwen Shapira (Confluent), Ted Malaska (Blizzard Entertainment)
Join the authors of "Hadoop Application Architectures" for an open Q/A session on considerations and recommendations for architecture and design of applications using Hadoop. Talk to us about your use-case and its big data architecture, or just come to listen in.
16:15-16:55 (40m) Ask Us Anything
Practical machine learning - ask us anything
Angie Ma (ASI), Anjali Samani (ASI), Marc Warner (ASI), Ken Williams (The ASI)
Pragmatic approach to data science, data science pipeline, and machine learning for different vertical applications. How to train existing staff to take on data science and engineering challenges. Where are the unicorns? How to find and hire great data scientists. How to evaluate their skillset. How to build and manage an innovative data...
9:00-17:00 (8h) Training
Apache Spark advanced training (Day 2)
Olivier Girardot (Lateral Thoughts), Sameer Farooqui (Databricks)
This three-day curriculum features advanced lectures and hands-on technical exercises for advanced Spark usage in data exploration, analysis, and building big data applications. Course materials emphasize architectural design patterns and best practices for leveraging Spark in the context of other popular, complementary frameworks for building and managing enterprise data workflows.
9:00-17:00 (8h) Training
Practical machine learning (Day 1)
Angie Ma (ASI), Marc Warner (ASI), Andrew Brookes (ASI Data Science), Anjali Samani (ASI), Alessandra Staglianò (The ASI), Ken Williams (The ASI), Mahesan Niranjan (University of Southampton), Elena Chatzimichali (Wellcome Trust Sanger Institute, Cambridge)
This intensive two-day course will provide you with a condensed introduction to the key concepts and techniques of machine learning. It will allow you to know what is and is not possible with these exciting new tools, and understand how they can benefit your organization. It will give you the language and framework to talk to both experts and executives.
8:00-9:00 (1h)
Break: Coffee Break sponsored by HGST
9:00-9:10 (10m)
Wednesday Keynote Welcome
Roger Magoulas (O'Reilly Media), Doug Cutting (Cloudera), Alistair Croll (Solve For Interesting)
Program Chairs Roger Magoulas, Doug Cutting, and Alistair Croll welcome you to the first day of keynotes.
9:10-9:25 (15m)
The data adventure in Santander
Maite Agujetsas (Santander Group)
In this presentation we will guide you through the data adventure that we have embarked on to deliver corporate goals. This digital transformation will help us to achieve customer experience and satisfaction improvement whilst adhering to security and data governance challenges to protect our customers.
9:25-9:35 (10m) Sponsored
Hadoop 2015: What we’ve learned in 5 years
Rick Farnell (Think Big, A Teradata Company)
After five years of enterprise adoption, Hadoop is now a critical data asset in your analytic and data platform strategy. Some companies, however, are struggling with making Hadoop work for their enterprise needs. . .
9:35-9:45 (10m)
Keynote with Cait O'Riordan
Cait O'Riordan (Shazam)
Cait O'Riordan, VP of product, music, and platforms, Shazam
9:45-9:50 (5m) Sponsored
Hadoop and healthcare
David Richards (WANdisco)
Healthcare is in the early stages of a revolution, as almost everything that determines our health is now becoming knowable. Data-driven healthcare represents an unheralded opportunity to make a huge leap forward. At this pivotal moment in medical history, we need to overcome an attitudinal aversion to utilizing the promise of data analysis to provide medical insight and save lives.
9:50-9:55 (5m) Sponsored
Bigtable’s next big step
Cory O'Connor (Google)
At Google, few things are so pervasive as Bigtable, the famous wide-column NoSQL database. It lies behind nearly every major Google product (Gmail, YouTube, Google Analytics), with its own class of internal memes, and a resource footprint unmatched anywhere else in the world.
9:55-10:05 (10m)
Keynote with Julie Meyer
Julie Meyer (Ariadne Capital)
Julie Meyer, chairman, CEO, and founder, Ariadne Capital
10:05-10:25 (20m)
Ideas that Matter
Tim Harford (The Financial Times)
We're always talking about "innovation", but - says Tim Harford - there are really two very different kinds of innovation. Using stories from sports, science, music, and military history, Tim will make you think different about where good ideas come from and how they should be encouraged.
10:25-10:55 (30m)
Break: Morning break sponsored by WANdisco
15:15-16:15 (1h)
Break: Afternoon break sponsored by Google
17:45-18:45 (1h) Events
Attendee Reception
Grab a drink, mingle with fellow Strata + Hadoop World participants, and see the latest technologies and products from leading companies in the data space.
12:25-13:45 (1h 20m) Events
Wednesday Lunchtime BoF Tables (located in the Monarch Suite)
Birds of a Feather (BoF) discussions are a great way to informally network with people in similar industries or interested in the same topics. (Located in the Monarch Suite)
19:15-21:15 (2h) Events
Data After Dark: Pub Crawl
The must-attend data party of year, Data After Dark is hosted by Strata + Hadoop World on Wednesday evening, at four venues in London: The Chapel, The Larrik, The Grand Union, and Lord Wargrave.
18:45-19:15 (30m)
Break: Dinner