All of our trainings are being held by Sönke Liebau or Lars Francke. For the hands-on parts we're working with a realistic cluster in the cloud and not with VMs on your laptops. All you need to participate in the hands-on exercises is a Laptop that can connect to our WiFi.
We offer our trainings in-house as well as publicly. Our fees are transparent and easy:
If you want a training for your team, we recommend doing it in-house This allows us to be flexible with the contents and the agenda according to your in-house wishes and technologies This way we can also talk about internal details that you can't talk about in public
The trainings we offer cover a broad spectrum of topics. But we're fully aware that for you and your use-case a different combination of topics might be even more interesting or economical. Therefore, we're more than happy to prepare and deliver a custom training for your needs. Just contact us if you're interested.
In this training we'll teach you about the Big Data ecosystem around the Apache Hadoop project. Hadoop is the worlds most used framework in the big data space. It consists of three components: Distributed storage of data, distributed computations and managing of computer resources. But that's not all: The ecosystem contains hundreds of tools and frameworks. The most important ones we'll present in this training. The training is independent of a specific distribution.
The hands-on part consists of simple commands to access HDFS as well as Spark jobs and SQL on Hadoop using Hive.
We offer this training with a length of 1-3 days:
Training to go with the book! We'll introduce you to HBase and will present the contents of the book "HBase: The Definitive Guide (Second Edition)" which was written by our partner Lars George. We also have hands-on exercises to help you test what you've learned. This also includes tests for the high-availability.
Training is delivered by a HBase committer.
We expect that you know the contents of the Hadoop & Big Data Basics training.
In two days we'll teach you the tools, frameworks and typical patterns used to load data into a Hadoop cluster.
We show you the most often used tools across distributions: Kafka (Streams & Connect), Spark (Streaming, Structured Streaming), HBase, Hive/Impala, HDFS, Sqoop, Oozie, Flume, NiFi. For each of these tools we'll talk about strengths and weaknesses as well as their position in the market and state of the distributions. Afterwards we'll teach you typical patterns of Data Ingestions in the Big Data/Hadoop world und will build a few simple flows in our hands-on exercises.
In this training we'll tech you the basic components and principles of Kafka, what you need to know about its administration and an introduction to the various tools from its ecosystem. We'll also talk about the differences between Apache Kafka and the Confluent Platform.
You'll learn your way around the command line interface to manage a cluster as well as best practices for your daily business. The participants will learn the theory of Kafka in-depths but will also be able to apply what they've learned on a real cluster. After we've learned the basics you'll get an overview of the existing 3rd party tools to ease the burden of administration and the possibilities of monitoring Kafka.
In addition to Kafka itself there are various tools in the ecosystem that are often used together. The course introduces you to the following projects in theory and practice:
For the hands-on part we'll use the Confluent Platform, but we'll mention the relevant differences to the Apache Kafka project.
There are many stories, misconceptions and myths around "Big Data" that often lead to failed or delayed projects. Projects that don't deliver what you'd hope or run over budget. This casual event is meant for managers that get to make decisions about Big Data projects at their companies. Our goal is to teach you the basics on what's possible today with "Big Data" (and what's not) as well as clear up a few of the common misconceptions.
The participants will learn everything they need to learn so that they can ask the right questions at the right time and to steer projects in the right direction.
Also - not unimportant - you'll get to have good food and the chance to network with your "comrades in misery".