Big Data training

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Our Big Data training is designed for everyone who would like to learn and test big data concepts and technologies and gain deeper practical knowledge. Since the training include practical exercises and we want to keep a high level of knowledge transfer, the number of participants is limited to 10.

SUMMARY

Poslovna inteligencija’s Big Data training is based on the perfect combination of theory and practice with a duration of 3 days.

During this training, participants will be introduced to the concepts, best practices which can be combined with real-world case studies and practical examples with lots of practical exercises and knowledge transfer sessions.

Our training is provided by leading practitioner experts. All of our trainings are based on our extensive practical knowledge and expertise within different industries and business segments with lots of practical examples and exercises.

AUDIENCE

Our Big Data training is designed for everyone who would like to learn and test big data concepts and technologies and gain deeper practical knowledge. Since the training include practical exercises and we want to keep a high level of knowledge transfer, the number of participants is limited to 10.

CONTENT

Day 1 – Business Aspect/Introduction

Results: Requirements definitions

  • Introduction
  • Way of Thinking in the age of Big Data
  • Concepts in Big Data Information System Design
  • Prerequisites for Big Data Information Systems
  • Overview of Big Data Platform Technology Vendors
  • Evolution of EDW systems and Data Lake concepts

Learning approach:

  • Concept Overview
  • Case Study

The way of thinking: Thing like  a Business Information System Design

Day 2 – Big Data Concept/Design – Structured Data

Results: Data collections, database design, management and monitor

  • Hadoop overview and Ecosystem
  • Proper Hadoop cluster configuration and deployment
  • Relational Data Analysis within Big Data platform, Analytical appliances
  • Modeling structured data as tables in Impala and Hive

Difference between batch processing and real-time data processing

  • Apache Kafka – Distributed streaming platform
  • Spark Streaming with Kafka and Hadoop

Learning approach:

  • Concept Overview
  • Discussions
  • Best Practice
  • Case studies
  • Practical exercises (Cloudera Manager, Hue, HDFS, Hive, Impala)

The way of thinking: Think like a Big Data Architect

Day 3 – Data Science and Data Visualization

Results: Using visualization to derive information from Big Data

  • Understanding Machine Learning
  • What is Machine Learning?
  • The Machine Learning process
  • A closer look to Machine Learning process
  • Machine Learning toolset
  • Practical workshop
  • Visualization and analytics in Big Data
  • Data storytelling
  • KPI Dashboards
  • Practical workshop (Tableau Software)

Learning approach:

  • Concept Overview
  • Best Practices
  • Practical Exercises – Tableau Software

The way of thinking: Think like a Data Scientist



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