Hadoop for Project Managers Training Course

Duration

14 hours (usually 2 days including breaks)

Requirements

  • A general understanding of programming
  • An understanding of databases
  • Basic knowledge of Linux

Overview

As more and more software and IT projects migrate from local processing and data management to distributed processing and big data storage, Project Managers are finding the need to upgrade their knowledge and skills to grasp the concepts and practices relevant to Big Data projects and opportunities.

This course introduces Project Managers to the most popular Big Data processing framework: Hadoop.  

In this instructor-led training in, participants will learn the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems. By learning these foundations, participants will  improve their ability to communicate with the developers and implementers of these systems as well as the data scientists and analysts that many IT projects involve.

Audience

  • Project Managers wishing to implement Hadoop into their existing development or IT infrastructure
  • Project Managers needing to communicate with cross-functional teams that include big data engineers, data scientists and business analysts

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Course Outline

Introduction

  • Why and how project teams adopt Hadoop
  • How it all started
  • The Project Manager’s role in Hadoop projects

Understanding Hadoop’s Architecture and Key Concepts

  • HDFS
  • MapReduce
  • Other pieces of the Hadoop ecosystem

What Constitutes Big Data?

Different Approaches to Storing Big Data

HDFS (Hadoop Distributed File System) as the Foundation

How Big Data is Processed

  • The power of distributed processing

Processing Data with MapReduce

  • How data is picked apart step by step

The Role of Clustering in Large-Scale Distributed Processing

  • Architectural overview
  • Clustering approaches

Clustering Your Data and Processes with YARN

The Role of Non-Relational Database in Big Data Storage

Working with Hadoop’s Non-Relational Database: HBase

Data Warehousing Architectural Overview

Managing Your Data Warehouse with Hive

Running Hadoop from Shell-Scripts

Working with Hadoop Streaming

Other Hadoop Tools and Utilities

Getting Started on a Hadoop Project

  • Demystifying complexity

Migrating an Existing Project to Hadoop

  • Infrastructure considerations
  • Scaling beyond your allocated resources

Hadoop Project Stakeholders and Their Toolkits

  • Developers, data scientists, business analysts and project managers

Hadoop as a Foundation for New Technologies and Approaches

Closing Remarks

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