Introducing Arcadia Enterprise 5.0 and In-Data-Lake, Cloud-Native BI

Wednesday April 10, 2019 | 10:00 am PDT/1:00 pm EDT/6:00 pm BST

Richard Tomlinson
Head of Product Management

Dale Kim
Senior Director of Products and Solutions

What to Expect?

With so many business intelligence (BI) platforms to choose from today, it’s easy to just stick with traditional technology from the most well known vendors. However, that assumes BI workloads are the same as they've ever been. But enterprises are rapidly finding out, in the world of big data, uniform workloads are a thing of the past.

Data lakes and cloud deployments are emerging as popular foundations for modern analytics and BI. To get the most out of your data, you need modern technologies built to take advantage of these architectures. You can’t rely on traditional technologies and processes of the past to get the fast time-to-insight that today's analytics can deliver.

In this webinar, we’ll discuss:

  • What in-data-lake cloud-native BI is, and why it’s different from traditional BI.
  • What advantages you get from BI in data lakes and the cloud.
  • Innovations in Arcadia Enterprise 5.0 designed for your modern analytic architecture.

Register Now

Richard Tomlinson
Head of Product Management
Arcadia Data

Richard currently leads Product Management for Arcadia Data with over 20 years experience in business intelligence and analytics software, data warehouse and data management platforms. His most recent work has been bringing to market new wave business analytics products on top of the Hadoop and Apache Kafka platforms. The entirety of his career has been occupied by software companies serving many roles including Product Management, Customer Services and Sales Engineering.

Dale Kim
Senior Director of Products and Solutions
Arcadia Data

Dale Kim is the senior director of products/solutions at Arcadia Data. His background includes a variety of technical and management roles at information technology companies. While Dale’s experience includes work with relational databases, much of his career pertains to nonrelational data in the areas of search, content management, NoSQL, and Hadoop/Spark, and includes senior roles in technical marketing, sales engineering, and support engineering.