Big Data

Analyst presentation by Brian Hopkins, Vice President and Principal Analyst at Forrester Research.

Denodo customer presentation by Luke Slotwinski, VP, Data & Analytics at Prologis.

Analyst Keynote by Rick van der Lans, Independent Analyst, Founder at R20 Consultancy

Attend this session to hear some of the most innovative use cases of data virtualization. Includes three customer case study presentations – get a chance to vote for most innovative use case to select the winner for this innovative award category.

Throughout his professional career, Manuel Lopez has held various engineering positions in multiple companies. Currently, he works as a Data Architect at Schaeffler. Manuel holds a Ph.D. in Computer Science. For more information about Manuel, visit his LinkedIn profile. https://www.linkedin.com/in/lopencarma/.Visit Denodo DataFest 2019 to watch all the sessions on-demand.

Customer presentation - Barney Eccleson, Senior Data Engineer, St. James’s Place Wealth Management

Harold works as product owner in the data management realm at Statistics Netherlands (CBS). He likes to think that his past as both IT developer and statistical researcher helps him in guiding useful product innovations at CBS. Before joining CBS almost twenty years ago, Harold studied political science and spent a couple of years working at a publishing agency.Visit Denodo DataFest 2019 to watch all the sessions on-demand.

Neil Sinclair is responsible for delivery of all BI Projects for NSS, fulfilling technical lead and team management roles. Analysis, design, development and implementation of systems are part of his responsibilities. His BI team undertakes numerous new projects each year to deliver new systems, as well as supporting and enhancing existing systems. For more information about Neil, visit his LinkedIn profile. https://www.linkedin.com/in/neil-sinclair-b747721b/.Visit Denodo DataFest 2019 to watch all the sessions on-demand.

Denodo customer presentation by Avinash Deshpande, Chief Software Architect at Logitech.

There’s a wide range of reasons why many organizations are deciding to modernize their data architectures. But they all agree on one thing: by using data more effectively, more widely, and more deeply, they can improve and optimize business and decision-making processes that will help them stay competitive in the emerging digital economy.To prepare data architectures for the next evolution of analytics, the current systems that rely on physical data movement and redundant data storage, must be modernized. However, for it to be effective, modernization must be seamless and must not disturb...