Description

The Advanced Big Data Analytics, Architecture, Management and Applications (ANDMA) v1.0 course provides students with architectural designs and advanced hands on training on topics covering Scaling of cluster to thousands of nodes and management, Lambda architecture for streaming analytics, Data Life Cycle management with HDFS tiered storage, and different approaches for Multi-tenant Hadoop cluster deployments with Openstack, UCSD Express, or with MapR volumes and Work-load Automation topics concerning the deployment of Big Data clusters.

It will cover the application and infrastructure architecture components for each use case with specific focus on Hadoop deployments. The training goes into details around UCSD Express end to end automation for big data. Also covers topics related with Best practices around Data Disaster Recovery as well as its security.

Objectives

After finishing this course, you will be able to:
  • Be able to scale up to thousands of nodes
  • Become familiar with Business Analytics including Splunk
  • Install and configure Red Hat, SPLUNK
  • Describe Edge Analytics (Social Media, IoT)
  • Describe SQL on Hadoop
  • Describe Data Life Cycle management for Tiered Storage of Hot, Warm and Cold data
  • Install Hadoop as a Service (on OpenStack)/Multi-tenant Hadoop cluster
  • Review End to End Automation with UCSD Express for Big Data
  • Describe Hadoop as a Service on Bare Metal
  • Describe Disaster Recovery
  • Apply Security

Outline

The course contains the following components:
  • Scaling to thousands of nodes - ACI
  • Analytics  Splunk
  • Edge Analytics (Social Media, IoT)
  • SQL on Hadoop
  • Data Life Cycle management - Tiered Storage of Hot, Warm and Cold data
  • Hadoop as a Service (on OpenStack)/Multi-tenant Hadoop cluster
  • End to End Automation with UCSD Express for Big Data
  • Hadoop as a Service on Bare Metal
  • Disaster Recovery
  • Security

Prerequisite Knowledge

Before taking this course, it is recommended that learners should be familiar with: