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.
How to Build a Multi Zone Data Sharing Platform
Paul Grooten, Data Architect, Statistics Netherlands (on behalf of Denodo)
In today’s data-driven world, Statistics Netherlands (SN) is confronted with a society characterised by the availability of powerful digital techniques and the presence of large amounts of data. In order to make maximum use of this, we offer both our own researchers and the external users this data richness in the form of “data as a service” with the experience of “data at your fingertips”. SN opts for a zone model, leveraging data virtualization, that offers maximum flexibility in the area of data governance as well as helping in the transition “from collect to connect” to your data.
Penn Room II
Why You Will Need a Dataware (and Why You Should Feel Urgent About It)
Martijn Kieboom, Senior Solutions Engineer, MAPR
In this session you will learn why it’s time to rethink how we deal with data today. The classic IT landscape consists of three different foundational layers. Even today these fundamental concepts haven’t changed, but the construct of these functional layers has.
In Part 1 we will show, how none of those evolutionary steps considered data as a first-class enterprise citizen:
• Applications have evolved over time from being monolithic to multi-tier to today’s connected network of distributed services weaved together through microservices
• Middleware has evolved from being purely a runtime layer for applications to being a layer for computational frameworks, orchestration engines and modern database technologies
• Hardware has shifted from being physical to virtual to delivered as a resource through a cloud-consumption model
Part 2: Learn from Real-Life Use Cases how enterprises decoupled data from the modern constructs of applications, middleware, and hardware these organizations got end-to-end control over data security, data placement, data access, data tenancy, and data controls completely independent from any other layer in the enterprise IT stack. This layer is called “Dataware”
Part 3: We will discuss significant business benefits of a Dataware:
• Reducing TCO by sharing a common data infrastructure across teams, departments, and workloads
• Providing consistent data governance and security enterprise-wide
• Delivering business-critical SLAs on open source and leverage modern tools
• Maximizes value from data with end-to-end controls on your most important digital asset
Penn Room I
The Rise of the Event-Streaming Platform
Mic Hussey, Senior Systems Engineer, Confluent
The data engineer tries to answer the problem of “how do I get hold of the data anyway?” For 20 years there have been two answers to the question. What’s the state of the art today and how will it evolve in the future?
Leeuwen Room II
The Path to Enterprise AI: Tales from the Field
Bart Koek, Solutions Architect, 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, Bart Koek, Solutions Architect at 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.”
Leeuwen Room I
Are you thinking Enterprise Data Cloud yet?
Wim Stoop, Senior Product Marketing Manager, Cloudera
To put enterprise data management in action and start creating value from analytics and machine learning, you need to be able to bring together everything you heard and saw today. The challenge is: how can you do this successfully while at the same time keeping control? The majority of organisations have to contend with a heterogeneous landscape of systems and infrastructures where business and regulatory demands add apparent complexity and conflict, making this a tremendous challenge. In this session, you’ll learn how to do just that. We’ll look at the characteristics for a comprehensive solution-set organisations demand that brings the right data analytics to data anywhere the enterprise needs to work, from the Edge to AI. An enterprise data cloud supports both hybrid and multi-cloud deployments, providing enterprises with the flexibility to perform machine learning and analytics with their data, their way, with no lock-in.
Goudriaan Room II
How to analyze 100% of your data while you are asleep?
Amit Levi, VP, 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