Seminar Schedule

2016 Seminar Guide, 2017 guide announced soon

The Big Data LDN seminar sessions are 30 minute presentations delivered by experts from the data industry. All seminars are free to attend on a first come first served basis.

The seminar schedule is a guide and subject to change, a final schedule will be made available at the event.

Seminar Schedule pdf download
09:45 - 10:20

Opening Keynote: The largest Big Data project in the Universe

When Big Data becomes Super Data - The largest Big Data project in the Universe. Bojan will discuss his role in the Square Kilometre Array Telescope, which will ingest 1 Terabyte of data per second. You'll learn how this team's pioneering work is defining the future of Data Engineering.

by Bojan Nikolic for SKA Telescope Project
10:30 - 11:00

Behind the Scenes Big Data Use Cases

Many businesses are looking for ways to put big data innovation to work to gain new insights or open new lines of business with less risk and less cost, but it isn’t easy to figure out what to do and how to do it. Talks on these topics generally fall into two groups. Some describe the advantages of big data in use-cases but at a very high level with very little detail. The other group consists of technological tours de force that are hard to relate back to the real world. This talk will take a different approach: I’ll provide a synthesis for a variety of real-world use cases that starts with a high-level description of business advantages but then pulls back the curtain to expose the practical and effective technical solutions that make it possible to integrate analytics with operations. I will disclose both sources and methods in this talk with the notable addition of a roadmap to guide you.

by Ted Dunning for MapR
10:30 - 11:00

Data Wrangling on Hadoop

As Hadoop became mainstream, the need to simplify and speed up analytics processes grew rapidly. Data wrangling emerged as a necessary step in any analytical pipeline, and is often considered to be its crux, taking as much as 80% of an analyst's time. In this presentation we will discuss how data wrangling solutions can be leveraged to streamline, strengthen and improve data analytics initiatives on Hadoop, including use cases from Trifacta customers.

10:30 - 11:00

Build Big Data Models in Minutes with BI Office from Pyramid Analytics

Lofty and academic discussion of Big Data is all very well, but in the end a business user needs to be able to create analytic models easily, quickly and simply, accessing data no matter where it might reside. Watch how analytic Models can be created in minutes and data analysed and visualised immediately for maximum business impact.

10:30 - 11:00

Data Warehouse Automation: Solve integration challenges, speed up time to market and save costs.

Hear Jos Driessen (formerly of Vodafone Netherlands) talk about the challenges in delivering new initiatives and changes much faster, improving data quality/freshness, all while reducing operating expenses. Hear how WhereScape is helping a number of organisations including Vodafone to solve integration challenges, speed up time to market and save costs.

11:10 - 11:40

“Medium” Data and Open Source Tech

MariaDB CTO Michael “Monty” Widenius will be presenting a keynote on building a business using open source technologies and the realities of “medium” data in today’s world using MariaDB.

11:10 - 11:40

Building a Culture of Self-Service Data Analytics

Organisations today collect massive amounts of data across all their business units, but often struggle with how to bring it all together to get a unified view of business performance. This is especially challenging when your organisation is entering new markets and needs analytics not only to view the business but to also understand its new markets and customers. Hear how Close Brothers, a leading merchant banking group, introduced a new analytics function to focus on their Retail Finance business and to grow the data blending and analytical capability throughout its organisation.

by Simon Hayter for Close Brothers
11:10 - 11:40

When Big Data Meets Fast Data

In the new world of Big Data, it’s not the big fish that eat the small fish, it’s the fast fish that eat the slow fish. In this context, the importance of best practice Big Data architecture that meets the needs of the business now leads the discussion. Understanding the differences between multiple vendors and platforms can be complex and a significant hurdle in starting your Big Data revolution. Attunity’s Ted Orme looks into the evolution of Hadoop and reviews the modern architectural journey from Lambda to Kappa; he’ll also share a number of real world use cases to bring this to life.

11:10 - 11:40

Process Revolution Starts in Big Data Underground

Parallel to the big data universe there is an invisible underground with often overlooked data. If you know how to look, you can uncover their priceless value to your business. These forgotten data contain deep insights into everything that is happening in your organisation and the opportunity to transform and improve all your business processes.

11:50 - 12:20

Designing databases for Cloud Applications

There are two sides of Big Data: operational and analytical. Operational data covers how you run your business, and analytical data involves generating insights from your operations. These are two different problems that require different approaches to solve them. Jonathan Ellis, CTO at DataStax will look at the requirements around operational and analytical data as part of cloud applications and how these issues are driving the next generation of operational databases that support a variety of data models.

11:50 - 12:20

IoT: From Data to Information; from Information to Knowledge

Industry 4.0 and the Internet of Things are certainly getting a lot of airtime lately. This session will cover building a predictive maintenance system for Hitachi Rail using “Big Data” eco-system elements. Concepts, processes, and ideas about how best to prototype such systems, and ways of collaborating between data engineering/integration/machine learning teams will be discussed. We can start to think about effective collaboration in this vacuum between data engineering and data science.

11:50 - 12:20

Big Data at IG – A Journey from Excel

This presentation will be whirlwind tour of the journey IG has gone through in Big Data. At the start, Excel sheets were the primary reporting mechanism, manually aggregating data from multiple sources, with business actions made manually, based on those reports. Today's system is an integrated, high volume, automated platform, used not only for reporting, but also to automate actions previously manually made, enabling real-time reactions and proactive predictions. The tour covers components we selected, the highs and the lows and why we selected some technologies over others. Also, we will take a quick dive into a sample project using Spark, covering the challenges and success it has given us.

11:50 - 12:20

Out of the Data Warehouses, and into the Data Lakes and Streams

As the amount of data explodes, traditional data warehousing and processing methods are starting to creak. Jeremy will look at how flexible streaming data processing has a bright future in the world of big data.

12:30 - 13:00

What “50 Years of Data Science” Leaves Out

We're told "data science" is the key to unlocking the value in big data, but, nobody seems to agree just what it is -- engineering, statistics, both? David Donoho's paper "50 Years of Data Science" offers one of the best criticisms of the hype around data science from a statistics perspective, and proposes that data science is not new, if it's anything at all. This talk will examine these points, and respond with an engineer's counterpoints, in search of a better understanding of data science.

12:30 - 13:00

Power BI – Become a Data Liberator

Demo-heavy session where you will learn how easy creating great looking, interactive reports can be. Whether you're a seasoned pro or just someone who’s used Excel, this session aims to demystify data mashup and ad hoc reporting.

12:30 - 13:00

Taming the Data Jungle; How to get from increasing numbers of raw data sources to accelerated time to insight

At what point does ‘Data’ become ‘Big Data’ and how do you keep this beast under control in a hyper-growth environment? From startup to global proposition with operations in APAC, EU and NA learn how retailer Swell took control of their data to produce super-fast turnaround on critical business reporting and insight. Learn how integrating, joining and analysing business critical multi-format, disparate datasets on a daily basis doesn’t have to take weeks of development time and how time to insight has been shortened down from months to days. By harnessing the depth and breadth of the Hadoop cluster and the intuitiveness of their modern BI platform from Datameer, Swell can process and store years of historical and new information and provide up to date reporting to the business. While the Data Jungle grows it becomes harder to manage and govern: With so much unstructured data being processed on a daily basis a single, innocuous change to a data map, pipeline process or metric calculation can result in large repercussions in changes further down the pipeline. Operating in multiple territories also brings its unique challenges to ensure compliance and security. Learn how Swell manages this in tandem to meet internal audit and compliance to provide a transparent and reportable data trail – including the continuous challenge of Data Preparation. To Swell, Datameer is more of a platform than application: Learn how Datameer with Hadoop provides the storage, processing power and analytical tools to harness the power of, control and govern their data – and witness the evolution of Swell’s Data Lake over time.

12:30 - 13:00

All data is equal – but some data is more equal than others

This session will explore the different ways in which data can be harnessed to provide valuable insights depending on the requirements of business users. It will discuss the acceptance that while all data is valuable, some data sets are ultimately more valuable than others and as such require a different approach when it comes to processing and analytics. Ultimately, the session will unveil the various tools and approachs in the market today that yield the best results.

13:10 - 13:40

V for… Victory. Deconstructing the big data myth

The assumed wisdom is that the origins of big data lie in the changing nature of data itself, described using various words beginning with V (volume, variety, velocity etc). In this presentation, Matt Aslett, research director for 451 Research, deconstructs the big data origin story with the aim of focusing attention on the real drivers of big data and describes how enterprises that focus on the new economics of data storage and processing have the advantage in working towards their ultimate aim: victory.

by Matt Aslett for 451 Research
13:50 - 14:20

The Beautiful Science of Data Visualisation

Seeing and understanding data is richer than creating a collection of queries, dashboards, and workbooks. It’s also more than just giving data to data scientists: it’s about giving data and the right tools to everyone in your business. In this talk you will learn how visual and cognitive science allow us to understand what makes data visualisation so deeply satisfying. Why does a collection of bars, lines, colors, and boxes become surprisingly powerful and meaningful? How does fluid interaction with data increase our intelligence? Join Andy for this fascinating talk in which he will explore why three decades of research into the beautiful science of data visualisation have brought us to the verge of an exciting new revolution.

13:50 - 14:20

Analytics on Steroids

Analytics is quickly evolving from being diagnostic to predictive and even prescriptive in nature, driving decisions at real-time speeds and influencing customer retention and growth strategies. Achieving this level of speed requires a technology and mindset shift towards next generation database software and hardware. This session discusses how to achieve real-time analytics, at scale and with extremely low latencies, with very little hardware, using powerful data structures and built-in analytic capabilities of Redis. Customers' real-time analytics scenarios including examples from Twitter, Pinterest, Snapchat as well as recommendations engine at a large scale and genome processing at a large university will be used to showcase the proficiency of these next-generation technologies.

13:50 - 14:20

Data Pipelines with Apache Kafka

Apache Kafka is recognised as the world’s leading real-time, high-throughput, scalable messaging system, adopted widely across thousands of companies worldwide. In this talk we will explain how Kafka works, investigate key architectural concepts, and discuss how to build streaming pipelines with Kafka as the data backbone.

13:50 - 14:20

Kick Start your Big Data project with Hyperconverged Infrastructure

Finding trends or new business opportunities from Big Data requires rethinking not only the application stack, but also the compute and storage infrastructure. The state-of-the-art Nutanix hyperconverged architecture with web-scale technologies delivers performance equivalent to bare metal deployments from your virtualised big data installations. Applications can linearly scale as your needs grow, enabling a pay-as-you-grow model. Nutanix creates Invisible Infrastructure by removing the complexities of deploying and managing the underlying platform, so data scientists can concentrate on analytics. Learn more about Hyperconverged Infrastructure and how to kick start your Big Data project.

by Ray Hassan for Nutanix
14:30 - 15:00

From Data Gravity to Data Agglomeration

Big Data is transforming all industries and facets of business whether it be with the flood of new data coming from sensors and IoT or predictive analytics and machine learning. Business models are being disrupted as data is changing how businesses operate, based on new, faster, and more accurate information. Combine this with the effects of agglomeration and you have a recipe for business disruption and transformation like no other. This must-see session dives into opportunities for innovation and things to watch around data and the agglomerative effects that surround it. The organisations that understand how to use data and agglomeration as a strategic weapon will be the winners in the new generation of business.

14:30 - 15:00

True Customer 360 with Apache Hadoop

Organisations spanning all industries are in pursuit of Customer 360, which aims to integrate and enrich customer information across multiple channels, systems, devices and products in order to improve the interaction experience and maximise the value delivered. With an Enterprise Data Hub, powered by Apache Hadoop, organisations can effectively stitch together a true 360-degree view of their customer base that goes beyond the traditional segmentation attributes in order to deliver personalised offerings, improve marketing effectiveness and drive down churn. What you will learn: * Current challenges with building a true Customer 360 * Highlight an iterative and proven methodology to effectively build a Customer 360 profile * Key Customer 360 use cases and industry case studies

14:30 - 15:00

Transforming Big Data into valuable Business Insights

Delegates will learn how to unlock and integrate a wider variety of data, using new cognitive computing strategies to uncover transformative business insights from multiple Big and Dark Data sources. Datawatch and IBM will be demonstrating unique integrated solutions designed for business users, data analysts and more advanced users, using the world of consumer marketing as the use case.

14:30 - 15:00

Living in, Working with and Loving Data

We spend our lives gathering data but have we stopped to think why? We not only need to gather we also need to understand that data and learn to be data literate. This session will talk about data literacy and what you need to do to encourage a data-driven organisation using self-service but not self-service anarchy.

15:10 - 15:40

Building a (machine) Data Fabric to enable data-driven decision-making

It’s often been said that without data, you’re just another person with an opinion. Before we can make a data-driven decision, we have to first collect data and make it accessible and usable. Next, we get value from the data by analysing it to enable us to make better decisions about the business. Machine data can inform decisions about predictive maintenance, optimisation of fuel usage in trains and can even help you make it to your flight on time. See how you can start your machine data journey today.

15:10 - 15:40

Proof of concept in weeks, data solution in months – How The Economist with Cloud BI and Looker have improved data-driven decision making

This session by The Economist Group, Cloud BI Ltd and Looker explores the challenges of data-driven decision making and how powerful the approach can be. Hear how the solution was implemented quickly and evolved in the cloud and the benefits of being able to see and understand customer preferences through a 360-degree view.

by Pete Grant, Sebastien Fabri, Bobby Gill for Looker, The Economist & Cloud BI
15:10 - 15:40

Unlock the Value of Your Data with BI Modernisation

Your enterprise is bursting with data and the tools to internally manage it. But can you actually turn your data into profit? GoodData will demonstrate how to drive your company's digital transformation, and bottom line, with Smart Business Applications - that leverage latest technologies to deliver cutting-edge data solutions across your B2B network.

15:10 - 15:40

Data-Driven Laundry?

How Berendsen uses the Microsoft IoT platform to drive Operational Efficiency.

by Duncan Macmillan for eBECS, Berendsen plc
15:50 - 16:20

The Digital Economy Happened, What’s the Next Disruptor?

The "Digital Economy" was a term coined in 1995. It's happened and the world is a vastly different place - try getting a taxi or buying a book. Now it's time for the next disruptor, The Algorithmic Economy. As data scientists and big data specialists, how do we get behind this next disruptor? In this discussion we look at not only The Algorithmic Economy, but how we can embed and distribute analytics across all of our data - big, streaming or anywhere else.

15:50 - 16:20

Making Machine Learning accessible to everyone with H2O’s open-source platform

- An introduction to H2O.ai (the company) and H2O (the platform) - A few use cases and feedback from users - New H2O products (all open-source): Deep Water and Steam

by Jo-fai Chow for H2O.ai
15:50 - 16:20

Harnessing the Power of Logs

Application logs are a rich source of information, often containing valuable insight into the operation of a system. Find out how Sky’s Platform Engineering team uses the Elastic stack to collect, index and visualise the application logs from their Customer Management platform.

by Chris Sale for Sky & Elastic
15:50 - 16:20

Making Sense of Big Data with Open Source Search

As data volumes grow it's increasingly important to be able to find interesting and useful patterns - and modern search engines are well placed to help. Charlie will describe how open source search engines such as Apache Lucene/Solr can be added to a Big Data system for search, classification, filtering, analysis and visualisation.

by Charlie Hull for Flax
16:30 - 17:00

Architecture Patterns for Big Data on AWS

With an ever-increasing set of technologies to process big data, organisations often struggle to understand how to build scalable and cost-effective big data applications. This session will help you choose the right technology to support each stage of your data’s lifecycle based on key criteria including data structure, design patterns and best practices.

by Ian Massingham for Amazon Web Services
16:30 - 17:00

The birth of the data-driven connected car

The connected car is now here and the autonomous car is just on the horizon. In this session, Steve will describe how Wejo, working with its big data partner Datalytyx, have created a real-time Modern Data Architecture founded on Talend, Cloudera and AWS technology to enable this fast-growing automotive industry start-up to exploit real-time big data streams and create innovative new journey-based products.

by Steven Pimblett for wejo Ltd
16:30 - 17:00

Using Machine Learning to feed hungry people – Tech Demo

There is often too much data to be able to understand it all by hand, and often it is difficult to see the interesting trees in the forest of data. Machine Learning gives us an opportunity to get computers to do this heavy lifting, and present us with key actions for operations. Machine Learning has many applications across a wide variety of fields – here we demonstrate hands-on with donuts how you can use Machine Learning to see deviations from expected donut consumption and either make more donuts or send out a targeted marketing campaign to get donuts off the shelves and into happy customers.

16:30 - 17:00

Tuning Search: Making the most of open source search and SOLR at Elsevier

Brought to you by Paul Groth, Disruptive Technology Director at Elsevier Labs.

09:45 - 10:20

Opening Keynote: Data Culture

Brought to you by Jonathan Woodward of Microsoft and Gary Richardson of KPMG. How do you become a data-driven organisation? The answer surely lies in building a corporate data culture, breaking down silos and data fiefdoms, sweeping aside outdated thinking. Jonathan and Gary explain how Silicon Valley-style digital transformation is going mainstream and what this means for your use of data.

10:30 - 11:00

Empowering People to Utilise Big Data with Data Wrangling

While Big Data technologies have generated a tremendous amount of excitement in providing organisations with a scalable platform to more effectively manage data of all shapes and sizes, Big Data's real impact will stem from innovations revealed through data-driven exploration conducted by a wide range of analysts within organisations. By empowering analysts to explore and interact with diverse data sources they previously never had the ability to work with, data wrangling solutions are essential to unlocking the true potential of organisational Big Data initiatives.

10:30 - 11:00

Laying down the SMACK on your data pipelines

You’ve heard all of the hype, but how can SMACK work for you? In this all-star lineup, you will learn how to create a reactive, scaling, resilient and performant data processing powerhouse. These applications involve distributed transactions with producers waiting for one or more consumers to respond. We will go through the basics of Akka, Kafka and Mesos and then deep dive into putting them together in an end to end (and back again) distributed transaction. Distributed transactions mean producers waiting for one or more of consumers to respond. On the backend, you will see how Apache Cassandra and Spark can be combined to add the incredibly scaling storage and data analysis needed for fast data pipelines. With these technologies as a foundation, you have the assurance that scale is never a problem and uptime is default.

10:30 - 11:00

Processing Financial Time Series Data with Google Dataflow (Apache Beam)

We are increasingly moving from batch-orientated analytics to stream processing and near real-time analysis. A trend that is set to accelerate as more and more production systems begin to incorporate machine learning, requiring us to be able to create models and run inference in a continuous stream of updates. In this talk we will discuss the work done on a recent proof of concept with a leading bank around the data engineering aspects of such a system.

by Reza Rokni for Google
10:30 - 11:00

Unlock the Value of Your Data with BI Modernisation

Your enterprise is bursting with data and the tools to internally manage it. But can you actually turn your data into profit? GoodData will demonstrate how to drive your company's digital transformation, and bottom line, with Smart Business Applications - that leverage latest technologies to deliver cutting-edge data solutions across your B2B network.

11:10 - 11:40

CIO / CDO Panel

Jessica Twentyman hosts the CIO / CDO Panel with Barry Green, CDO of Bank of Ireland, Cathy McCabe, CIO of Jaeger, Omid Shiraji, CIO of London Borough of Camden and Jason Foster, CEO of Cynozure. Our expert panel discusses the vital role of data in modern organisations and whether new hybrid business/IT leaders such as Chief Data Officers are required to complement the work of CIOs and their teams. We hear the views of data specialists and of CIOs from public and private sector organisations.

by Omid Shiraji, Cathy McCabe, Jason Foster, Barry Green, Jessica Twentyman for Cynozure, Bank of Ireland, Jaeger & London Borough of Camden
11:10 - 11:40

Using Machine Data to understand customers and improve Customer Experience

Machine data can tell us a lot about the interactions customers have with us. At Splunk, we see many of our customers using Machine Data to make their services run better and to secure them; they can also use the same machine data to understand key customer metrics like usage frequency, engagement and feature usage, sophistication of use and customer focused performance. Taking this a step further by looking at customer reported experience and demographic data from CRM we can build models that show how these objective metrics contribute to subjective customer experience.

11:10 - 11:40

Business Intelligence in an Omni-Channel World

This session will explore a best practice example of how four high street brands overcame data challenges, combining years of historical data (down to receipt level) into useful information for making better informed business decisions in a single environment. High street retailers sit on huge volumes of business data, with the situation only exacerbated when multiple brands and channels to market exist. Everything from loyalty card data, units per transaction, margin analysis, footfall conversion and basket analysis historically reside in multiple spreadsheets and archaic business information systems. The challenge for omni-channel retailers is how to effectively analyse and cross-reference this data to make sensible, informed decisions around business strategy. This session will explore the use of technology to analyse data and then seamlessly move into budgeting, planning, forecasting, simulation and predictive analytics.

by Shirley Wills for BOARD International, Retail Assist
11:10 - 11:40

Industrial IoT and the Energy Sector

Wael will discuss some of Pentaho’s recent collaborations within the energy sector on diverse topics such as predictive maintenance, dynamic energy pricing, and total asset optimisation. The discussion will cover technology, machine learning, and evolution from anomaly detection to more robust systems.

11:50 - 12:20

How-to enable sustainable IT & Business collaboration around real-time data

Is it just us, or has all data gone real-time over-night? The modern data platform now requires instant data access for both business and IT. However, traditional architectures were not designed to meet this demand. Some people immediately jump to Big Data and the Data Lake as the answer, but major roadblocks exist, particularly when it comes to data governance and security. Add to this the need to ingest large data sets and make results available in real-time to customer-facing applications… you have to fundamentally rethink things. Come to this session to learn how Talend and Datalytyx address these issues for some of the UK's largest firms.

11:50 - 12:20

UBS: Deeper & Quicker Insights with Alteryx Data Blending for Tableau

The IT group at UBS has been challenged to become a service provider to the rest of the organisation, including allowing business groups to make informed decisions about their IT investments. Before using Alteryx it would take days of work to deliver views of spend or the impact of investments. With Alteryx similar tasks take hours or minutes. And the data can come from many more sources, providing even deeper business insights. Attend this session to hear the experience of one Tableau expert’s journey to self-service analytics with Alteryx.

by Nick Bignell for Alteryx, UBS
11:50 - 12:20

Build Big Data Models in Minutes with BI Office from Pyramid Analytics

Lofty and academic discussion of Big Data is all very well, but in the end a business user needs to be able to create analytic models easily, quickly and simply, accessing data no matter where it might reside. Watch how analytic Models can be created in minutes and data analysed and visualised immediately for maximum business impact.

11:50 - 12:20

Streaming Goes Mainstream: How Stream-First Architecture & Emerging Technologies Provide a Competitive Edge

Among changes involved in becoming a data-driven business, there’s a new revolution: working with streaming data as a widespread aspect of an organisation. No longer is streaming data seen as just a special use case. It’s increasingly commonplace for businesses to collect streaming data from a variety of sources, ranging from IoT sensors to familiar clickstream data, and to use new methods for stream processing to analyse that data. In short, streaming is becoming mainstream. And, surprisingly, the value of streaming data goes far beyond just real-time insights. This talk takes a look at the advantages of stream-first architecture and the importance of message transport in this approach, including how it can support microservices. We’ll also examine some emerging technologies such Apache Kafka and MapR Streams for message transport and Apache Flink for real-time and batch processing.

12:30 - 13:00

The Art of Big Data Leadership

To really get value out of big data a range of leadership capabilities are required to define, deliver and iterate your strategy. This session will explore the different lenses on leadership and how the Chief Data Officer brings those together.

12:30 - 13:00

Stream processing with Apache Flink

In this talk, Kostas will cover the basics on Apache Flink: why the project exists, where it came from, what gap does it fill, how it differs from all the other stream processing projects, what is it being used for, and where is it headed. In short, streaming data is now the new trend, and for very good reasons. Most data is produced continuously, and it makes sense that it is processed and analysed continuously. Whether it is the need for more real-time products, adopting micro-services, or building continuous applications, stream processing technology offers to simplify the data infrastructure stack and reduce the latency to decisions.

by Kostas Tzoumas for data Artisans
12:30 - 13:00

Transforming Big Data into valuable Business Insights

Delegates will learn how to unlock and integrate a wider variety of data, using new cognitive computing strategies to uncover transformative business insights from multiple Big and Dark Data sources. Datawatch and IBM will be demonstrating unique integrated solutions designed for business users, data analysts and more advanced users, using the world of consumer marketing as the use case.

12:30 - 13:00

Accelerating Machine Learning For Real Time Applications

Machine learning harnesses the increased computing power of today’s hardware to produce predictive intelligence, applying known patterns and knowledge to changing scenarios while evolving to apply new learning. Join this session to learn how common practices in machine learning such as running a trained model in production can be substantially accelerated and radically simplified by using databases that are adapted to storing and serving common models generated by ML algorithms. We will also discuss the implementation of simple, real time feed forward neural networks with Neural Redis and typical scenarios that can benefit from such efficient, accelerated artificial intelligence.

13:10 - 13:40

The Value of Transforming into a Data-Driven Business

Organisations have more data at their disposal than ever before, from sources both inside and outside the company. Yet making sense of it all and driving business value has been a challenge with traditional ways of working. Alex Bartfeld from Cloudera will share practical examples of organisations that have adopted a modern approach to data in order to address boardroom initiatives around customer insight, product and service innovation and lowering business risks. Join this session to learn how you can develop a modern data strategy and transform your organisation to a data-driven business.

13:20 - 14:20

How to build a Data Discovery Hub without scripting and in under 30 minutes

In this era of big data, the last thing organisations need is more data. However, there is a growing need for better data quality. Users need fully prepped and governed data that enables them to make immediate and accurate data-driven decisions. And old-fashioned, rigid data warehouses can’t always guarantee the right data at the right time. The modern Data Discovery Hub, however, helps organisations access, model and govern data automatically - all without long-winded scripting or manual data building. Join Differentia Consulting as we build an agile Data Discovery Hub during this session, right before your eyes. See just how easy it is to implement a fully governed data platform - no scripting required. Includes an introduction, demo and Q&A session.

13:50 - 14:20

Data for Good – the JustGiving story

Brought to you by Mike Bugembe, Chief Analytics Officer at JustGiving.

by Mike Bugembe for JustGiving
13:50 - 14:20

Kafka Streams: the new smart kid on the block

Kafka Streams is a new stream processing library natively integrated with Kafka. It has a very low barrier to entry, easy operationalization, and a natural DSL for writing stream processing applications. We will provide the audience with an overview of Kafka Streams including its design and API, typical use cases, code examples, and an outlook of its upcoming roadmap. We will also compare Kafka Streams' light-weight library approach with heavier, framework-based tools such as Spark Streaming or Storm, which require you to understand and operate a whole different infrastructure for processing real-time data in Kafka.

13:50 - 14:20

Apache Hadoop Meets Cybersecurity

Description: Cybersecurity has become the topic of conversation for organisations across every industry as attack surfaces have expanded with the digital, social, and mobile world. As it becomes more difficult to protect organisations, professionals are turning to new technologies in order to avoid massive reputational, monetary, and intellectual property losses. In recent years a convergence of factors have occurred that is putting Apache Hadoop and Apache Spark at the forefront of the cybersecurity arms race. What you will learn: * Learn how Hadoop can modernise your existing cybersecurity architecture * Detect advanced threat faster by deploying advanced analytics across PBs worth of data * Reduce threat investigation and mitigation time with comprehensive data access

14:30 - 15:00

GDPR & Privacy Debate

Brought to you by our expert panel. When does Big Data become too intrusive for individuals and society? What are the ethics of harvesting and using all this personal data? What do consumers really think about business use of their data? And what do you need to do to comply with rapidly-changing international data protection laws? Moderated by Paul Fisher, Research Director at PAC UK.

14:30 - 15:00

The Spark Technology Center: What we’ve been working on and future plans

In June 2015 IBM announced a major commitment to Apache Spark, calling it "potentially the most important new open source project in a decade". As part of this commitment, IBM established the Spark Technology Center (STC) in San Francisco, where engineers, committers, and designers contribute to Apache Spark and the open source community. In this session we will talk about the work that's being done at STC and we will provide an update on what's hot, what's new and what's on the roadmap for 2017.

14:30 - 15:00

Case Studies of Business Transformation through Big Data

Every industry, every organisation, every department is going through a huge change, whether realised or not, as the opportunity to harness data to impact their business is ripe. Many businesses are successfully leveraging new platform technologies to transform their organisation using data. Whether they are renovating their existing infrastructure for substantial cost savings or innovating their architecture to find new business opportunities the impact is undeniable. In this session we will review the industry trends as well as highlight transformative business use cases, including Centrica and Royal Mail, drawn from a wide range of market sectors across Europe to bring the future of data to life.

14:30 - 15:00

Driving FIA Formula E Championship Fan Engagement with IoT Data

The opportunities to deliver customer value through IoT are incredibly exciting but the challenge of architecting infrastructure to support these initiatives is just as daunting. In this session we will help you close the gap between the infrastructure required to support IoT devices and the ability to monetise your IoT Time Series data just by picking the right database. Discover how at the FIA Formula E Championship race Intellicore collects raw data from the pioneering electric racing cars, providing spectators with live statistics and analysis as the race takes place using Riak TS, a NoSQL database optimised for IoT. Get some best practices in IoT Data Modeling and a live demo and coding examples of storing, retrieving and integrated analytics with Apache Spark.

15:10 - 15:40

Data Science Skills and Careers Panel Debate

Brought to you by an expert panel including Kim Nilsson, CEO of Pivigo and Jez Clark, Co-Founder and Director at Eden Smith. Are we facing a serious skills shortage in the UK big data and data science industry? Does Brexit make this worse? Our panel debates what employers can do to secure the best data talent and offers advice to ambitious professionals on how to secure the best roles.

15:10 - 15:40

The Future of Microsoft Advanced Analytics

Come and glimpse the future with this business-focused session where we will look at how Microsoft and its customers are using the newest technology to innovate and drive a change toward a data-driven culture. See the plethora of tools and services available to initiate this change in your businesses as well as a demo of the simple yet powerful free visualisation tool, Power BI.