Big Data Moscow 2018

Ernestas Sysojevas

DATA MINER, Lithuania

Date: October 10, 2018
Time: 10:00-17:00
Language: Russian


Ernestas is a Senior Trainer and Director in DATA MINER Company. His training carrier started 15 years ago in Lithuania as Certified Microsoft Trainer (MCT) with specialization in Relational Databases area. During these years, he delivered more than 300 Microsoft SQL Server courses. However 5 years ago he decided to step from Relational Database word toward Big Data solutions.

Now he delivers official Cloudera Hadoop trainings not only locally in Lithuania but in all Europe from London to Moscow. As Big Data technology enthusiast, Ernestas often speaks or delivers workshop trainings in various IT conferences and events. In 2016 year, taking into account course attendees’ evaluations, Ernestas was awarded as the best Certified Cloudera Hadoop trained in EMEA area (Europe, Middle East and Asia). He is one of inspirers and main organizers of,, and conferences.


Essentials for Apache Hadoop and Hadoop Ecosystem

Learn how Apache Hadoop addresses the limitations of traditional computing, helps businesses overcome real challenges, and powers new types of big data analytics. This workshop introduces Apache Hadoop ecosystem and outlines how to prepare the data center and manage Hadoop in production.


  • Why Hadoop is needed
  • The Hadoop’s architecture
  • What type of problems can be solved with Hadoop
  • What components are included in the Hadoop ecosystem
  • Core Hadoop: HDFS, MapReduce, and YARN
  • Data Integration: Flume, Kafka, and Sqoop
  • Data Processing: Spark
  • Data Analysis: Hive and Impala
  • Data Exploration: Cloudera Search
  • User Interface: Hue
  • Data Storage: HBase
  • Data Security: Sentry
  • Managing Hadoop


There are many components working together in the Apache Hadoop stack. By understanding how each functions, you gain more insight into Hadoop’s functionality in your own IT environment. We will go beyond the motivation for Apache Hadoop and will dissect the Hadoop Distributed File System (HDFS), MapReduce, and the general topology of a Hadoop cluster. Various projects make up the Apache Hadoop ecosystem, and each improves data storage, management, interaction, and analysis in its own unique way. We will review Hive, Pig, Impala, Spark, Kafka,  Flume, Sqoop, HBase and Oozie, how they function within the stack and how they help integrate Hadoop within the production environment. We will share several Hadoop use cases across a few industries including financial services, insurance, telecommunications, intelligence, and healthcare to learn how Apache Hadoop is used in the real world and will explore ways to use Apache Hadoop to harness Big Data and solve business problems in ways never before imaginable. It is critical to understand how Apache Hadoop will affect the current setup of the data center and to plan ahead. We will discuss what resources are required to deploy Hadoop, how to plan for cluster capacity, and how to staff for your Big Data strategy. Once you have Hadoop implemented in your environment, what’s next? How do you get the most out of the technology while managing it on a daily basis? So, we will learn how to manage Hadoop in effective way.

Target audience

This introductory workshop is intended to all IT professionals with little knowledge about Hadoop and who are interested to know the theory behind the creation of Hadoop, the anatomy of Hadoop itself, and an overview of complimentary projects that make up the Hadoop ecosystem.

Course prerequisites

A personal computer with 16 GB of RAM (8 GB is minimum) for virtual machines.

Date: October 10, 2018