Hadoop to Dataproc Breakfast Seminar
Learn all about migrating existing on-prem workloads to Google Cloud Dataproc and run Apache Spark and Apache Hadoop in a faster, easier, and more cost-effective way.
Hadoop to Dataproc Breakfast Seminar
What: Breakfast Seminar
Where: Binx.io Amsterdam, Wibautstraat 200, Amsterdam
When: 27 March, 7:30 - 10:00
During this seminar, experienced cloud architects will introduce Google Cloud Dataproc, share their experience with migrating on-prem workloads to the cloud, and discuss the differences between Dataproc and Dataflow.
Join this workshop if you are interested to learn about the best strategies to move existing Hadoop workloads to GCP, so that you can benefit from increased cost-efficiency, extremely scalable compute-power, and per-second billing.
What You'll Learn
During this seminar, you will learn:
The features of Dataproc for data processing, analytics, and machine learning;
Strategies to move existing workloads to Dataproc;
Best-practices of refactoring existing on-prem workloads to optimally benefit from the flexibility that the cloud provides;
The differences between Cloud Dataproc and Cloud Dataflow.
- 7:30 - 8:00 Welcome and Breakfast
- 8:00 - 8:15 Opening by Bart Verlaat, Binx.io
- 8:15 - 8:30 Introduction to Google Cloud Platform - Rokesh Jankie, Google Cloud
- 8:30 - 8:50 Customer Story
- 8:50 - 9:10 Dataproc versus Dataflow - Wietse Venema, Binx.io
- 9:10 - 9:30 Processing a terrabyte of data in less than 15 minutes - Constantijn Vicinescu, Binx.io
- 9:30 - 10:00 Best-practices to migrate existing workloads to Dataproc - Niels Zeilemaker, GoDataDriven
- 10:00 End
Fill in this form to register for this breakfast seminar:
Google Cloud Dataproc
Google Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that is fast, easy to use, and low cost.
The Spark and Hadoop ecosystem provides tools, libraries, and documentation that you can leverage with Cloud Dataproc. By offering frequently updated and native versions of Spark, Hadoop, Pig, and Hive, you can get started without needing to learn new tools or APIs.
For more information about Cloud Dataproc: https://cloud.google.com/dataproc/
Rokesh Jankie is passionate about Google technology and enjoys being a Customer Engineer Google Cloud at Google Amsterdam. His passion for Machine Learning started during his study at the Leiden Institute of Advanced Computer Science (LIACS) where he first encountered Neural Networks in 1997. At Leiden University, Rokesh graduated in Computer Science (MSc.) on optimization problems and algorithms.
Wietse Venema is a senior cloud engineer at Binx.io. With a background in Informatics (Ba) and Software Engineering (Msc), he naturally applied his skills as a full stack developer for companies like ING and Intergamma (both via Xebia), where he specialized in Google Cloud Platform.
As a Google Cloud Consultant at Binx.io, he is currently the GCP Lead at Booking,com. Constantijn is an all-round IT professional with significant experience in development, design, architecture, and consultancy.
Constantijn enjoys working with teams to achieve a high level of quality and productivity and is capable of dealing with the communicative and interpersonal challenges to help teams reach that point.
Niels is Chief of Technology at GoDataDriven and works for a wide range of companies where he engineers features and builds models.
Niels finished his PhD thesis at the Technical University of Delft where he researched into P2P systems, primarily focusing on privacy and cooperation, including applying encryption and anonymization techniques in the P2P domain.
Niels is experienced in various programming languages such as Python, Java, C#, R.
Bart Verlaat is the managing director and co-founder of Binx.io. As a graduated engineer, he led the initiation and implementation of the KPN “ZorgCloud” solution, which delivers specific Cloud services, tailored to a large variety of care professionals working from 4.500 connected healthcare institutions.
Before he founded Binx.io, he worked as a business development manager for Google Cloud.
Starting to use Google Cloud Dataproc is really simple, before you know it you're up and running. Migrating existing workloads to Dataproc is a different cup of tea, and requires a solid migration strategy.