Manual configuration of public and private subnet, routes, security groups, nat gateway and bastion server via de AWS console
Scalar provides training for those who are interested in big data and willing to learn the fundamentals quickly without having to spent months to accumulate the knowledge to get productive. Our trainings will give you a jumpstart into big data.
During the training we make use of a self assembled sandbox with all necessary software that is already installed and configured. The Sandbox does contain all the training materials, examples and practises which will also be available for the student after the training. This way the student is not left alone in the dark after the training because they can practice what they have learned during the training on their own pace with the sandbox that is provided to them, this way they can become immediately productive.
In this training we will explore the Spark framework, you will learn how it can be used to read, transform and store data.
Via hands on examples you will get experience in using Spark to transform data in different formats to answer certain questions and store it in different destinations.Futhermore you will experience different ways to visualize your data and how to deploy your Spark programs.
The target audience for this training are software engineers, data engineers, analysts, architects and technical managers who like to get a hands-on overview of the Apache Spark framework.
Duration of the course: 2 days
Download the training brochure: Introduction training Spark
Gabi S. 06-01-2016
"Spark was completely new to me, but this training made me realize that it is a very powerful framework and it has a lot of potential for certain use cases we encounter at our clients. The training is well organized and builds up your knowledge on Spark progressively on basis of theory and exercises.It will give you a good insight where Spark fits into the ecosystem how it evolved and for what kind of tasks it is being used."
Ioan M. 06-01-2016
"I enjoyed the training about Spark very much since it was my first introduction to it. The theory helped me understand why Spark is so popular and for what business case scenarios it is being used. What i especially enjoyed was working with a lot of new technologies via exercises and see it all come together, normally you won't get this out of a training. I am excited to start working on my first Spark based solutions on basis of the information i got out of this training."
In this training we will explore the basics of the big data ecosystem, the different distributions and the different components.
Via hands on examples you will get experience in loading data into the Hadoop File System, work with different file formats, load data into Hive and learn the basics about building a EDW with Hive.
The target audience for this training are software engineers, data engineers, analysts, architects and technical managers who like to know more about the big data ecosystem.
Duration of the course: 3 days
Download the training brochure: Introduction training big data
Gabi S. 23/12/2016
"The training about big data was very informative. Progressively builds your knowledge base on big data and related concepts. It will give you a good insight on the fundamentals to start as a beginner, even more advanced people could benefit from learning some useful tips."
Ioan M. 23/12/2016
"Before i joined the training i didn't know much about the big data ecosystem. The training helped me to understand the concepts and technologies, it gave me the information i hoped for so i could get started and i am currently working with these technologies and tools and keep improving my knowledge about it. I consider the best part of this training the practical exercises which you don't have with other trainings, in my opinion this is a very strong point for any technical training."
Our training locations are Enschede and Deventer. On request training can be supplied on the location of the customer.
Contact us in case you're interested in our trainings, we would be glad to answer your questions.
per mail via: [email protected]
per phone: +31(0)630748787