Duration: 16 hours / 2 days
Knowledge: Beginner
Trainer: Marko Ć tajcer
Training Methods: Virtual Class

Ignore the skills of working with leading world technologies in the field of Big Data! In this training, you will need to use Big Data for data collection and data analytics to take advantage of the potential of your business.

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Overview

Our Big Data training is based on the perfect combination of theory and practice. Students will learn about the modern Big Data concepts and best practices combined with examples of Big Data analytical systems implementation in different industries and a host of examples that include practical exercises using Cloudera platform. Education encompasses the entire process of data loading up to integration, structuring and data analysis using the latest Big Data technologies.

Audience

This training is intended for anyone interested regardless of previous knowledge, whether you are a beginner in the field of Big Data analytics or you want to upgrade your knowledge.

What you will learn

After training, student will understand the architecture of Big Data systems and how to apply methods for analyzing large data over their own data sets and business cases. Also, student will learn how to use real-time tools and techniques to process data and how to manage large data efficiently.

Syllabus

In this module you will learn what is the Big Data analytics, where to apply it, how to use it, and which technologies to choose from.

  • Workshop

In this module, you will learn the concepts of great data and learn how to process structured and unstructured data. You will learn the Data Lake concept and the principles of work and the benefits of MPP technology.

  • Workshop

In this module you will learn how to use streaming data technology to get the information you need in a timely manner. In this module you will learn the concept of Publish-Subscribe mechanisms and data processing in the stream.

  • Workshop

In this module you will learn which best practices of managining large amount of data, and how to maintain large data analytics systems in production.

  • Workshop

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