This event is co-located with Cloud Native: Delivering Effective Enterprise Solutions. Delegates may attend any sessions from either of these two conferences.
“A data lake is a system or repository of data stored in its natural format, usually object blobs or files. A data lake is usually a single store of all enterprise data including raw copies of source system data and transformed data used for tasks such as reporting, visualization, analytics and machine learning.” (Wikipedia)
As the definition shows there is considerable work to be done to create a comprehensive strategy and architecture to use the stored data. But this can be daunting task as every enterprise will have to deal with the innumerable technologies, stakeholders as well as prioritize their efforts in making the changes.
This conference will help you:
The day will be a mixture of mini-workshops and presentations covering:
We are inviting speakers – thought leaders, subject experts and start up entrepreneurs – to share their knowledge and enthusiasm about their work and their vision in the field of Data.
Please complete the speaker’s response form and submit a proposal to present at this event.
Our approach is that our events are dedicated to providing a harassment-free experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity or religion. We do not tolerate intimidation, stalking, harassing photography or recording, sustained disruption of sessions or events, and unwelcome physical contact or sexual attention. We do not tolerate harassment of conference participants in any form. Sexual language and imagery is not appropriate for any conference venue, including talks, workshops, Twitter and other online media. Event participants violating these rules may be sanctioned or expelled from the event without a refund at the discretion of the conference organisers. Please bring your concerns to the immediate attention of the event staff.
Diversity: In our endeavour to be the provider of knowledge to the business community, we understand that this depends on hearing from and listening to a variety of perspectives that come from people of all races, ethnicities, genders, ages, abilities, religions, sexual orientation, and military service. We welcome diverse speakers for all our events, we do not always fully achieve this goal, but it is an ongoing process.
Richard Conway, Chief Executive Officer, Elastacloud
Organisations now look to the Data Lake as the new single version of the truth where they looked as they used to look to a Data Warehouse. In this plenary Richard Conway will assess why every organisation needs to shift their thinking to accessibility of data as the source for all other sources. You will learn all terms and ideas of Data Lake related to design and implementation as well as dos and don’ts. An arsenal of words and good practice that every executive should have in their war chest!
Dominic Harries, Dev Lead, IBM
What does it mean to be cloud native? This talk will explain the whats and whys of building cloud native applications, and examine how the best ways to organise people sometimes mirror the best ways to organise code.
Huw Price, Managing Director, Curiosity Software Ireland
For all the promise of AI, we must first have enough varied, quality data being collected across the enterprise. Remove siloes, maximise observability. Then harness insights. This session will present a practical strategy for creating a healthy data lake, using Robotic Process Automation (RPA) to connect disparate technologies and stakeholders.
Mark Wilcock, Founder, Zomalex
Norbert Eschle, Enterprise Data Architect, Direct Line Group
Most organisations are at the very least considering the move of some or all of their data capabilities to the cloud. This offers agility and the opportunity to explore, test and implement new ways of working. It also challenges Enterprise Architecture to support technology change in new ways. This talk will share some of these challenges and how they can be addressed.
♦ Why should you rely on data integration infrastructure to make the Data Lake work
♦ Machine Learning for Smarter Enterprise Data
♦ Data Governance & Data Catalogue
♦ Data Lake vs Data Warehouse
♦ Securing the Data Lake
♦ Future proofing Data Warehousing
♦ Agile approach to Data Management
♦ Harnessing NoSQL, Hadoop, Spark and beyond: Tools that co-exist with these applications.