Wednesday 19th June 2019

The Seminars will take place from 12.15 – 13.00.
Delegates will be able to attend one seminar at the event. No pre selection is required – delegates will be able to select which session they attend onsite.



Victoria (Main Conference room)
Sponsored by:
The Path to Enterprise AI: Tales from the Field

Larry Orimoloye, Dataiku

Enterprise AI is a target state where every business process is AI-augmented and every employee is an AI beneficiary. But is that really attainable? And, if so, what is the path to get there? In this talk, Dataiku will share learnings from the field, describing how companies of different sizes and across different sectors have begun this journey. Some are farther along than others, and by making the right decisions now and avoiding stumbling blocks, you can supercharge your quest to this AI-fuelled future.


Edward 1
Sponsored by:
Transactional and Analytics together: Understanding the Architecture of MariaDB ColumnStore

Maria Luisa Raviol, Senior Sales Engineer, MariaDB Corporation

MariaDB ColumnStore extends MariaDB Server, a relational database for transaction processing, with distributed columnar storage and parallel query processing for scalable, high-performance analytical processing. This session helps to understand how MariaDB ColumnStore works and why it’s needed for more demanding analytical workloads.


Edward 3
Sponsored by:
Data Strategies for Big Data & Analytics in a Hybrid/Multi Cloud World

Patrick Callaghan, Business & Technology Strategist, DataStax

How to support any cloud strategy with a data strategy that exploits hybrid and multi-cloud, breaks down data silos. In this session learn the pros and cons of today’s most popular enterprise data strategies for a hybrid/multi cloud world: before, during, and after the move.


Edward 5
Sponsored by:
How to Deliver Trusted Data at Speed

Darren Brunt, Pre-Sales Director, Talend UK&I

In the era of the information economy where data has become the most critical asset of every organization, how can you accelerate its speed to stay at the cutting edge without compromising the business trust that fuels your insights and actions?

In this session, Darren will discuss and demonstrate using a single suite of apps how you can shorten the time to trusted data, including:

  • How to better collect data across systems
  • Govern it to ensure proper use
  • Transform it to new formats and improve quality
  • and more effectively share it with internal and external stakeholders


Edward 7
Sponsored by:
How to Analyze 100% of Your Data While You Are Asleep?

Amit Levi, Vice President, Head of Product and Marketing, Anodot

  • Learn how leading companies offload the effort of analytics to AI “workers”
  • How to reduce noise and achieve more accurate analytics using technologies which were becoming available just now


Albert 1
Sponsored by:
Maximize Advanced Analytics and Machine Learning Potential by Leveraging Data Virtualization

Vincent Fages Gouyou, EMEA Product Management Director, Denodo

Machine learning elicits mixed reactions, some consider it a company’s new super power while others see it as an overhyped fad which fails to deliver. While both can be true, companies need to factor in machine learning to obtain better insights from their data and stay competitive, and therefore need to look for a way to optimize its potential.

Advanced data science techniques, such as machine learning, are in fact useful tools that can help to derive valuable insights from existing data. If complemented with data virtualization, machine learning can live up to its potential without putting the pressure on the data scientists to look for and transform the right data.

In this session, we will explain exactly how data virtualization can be used to get the information needed in a more efficient and agile manner, show you the value added by this technology via a short demonstration, and finally present a real customer success story of this use case.

We’ll answer the following questions, and more:

  • How can data virtualization help deal with large volumes of data more efficiently?
  • How does data virtualization help data scientists accelerate data acquisition and preparation?
  • How is McCormick, a food flavoring giant, using data virtualization to season its machine learning and blockchain landscape?