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Introduction to Big Data and NoSQL

 

Course Description | Course Outline | IT Training

Course Outline

Day 1 - Morning

Big Data Foundation and Market Pulse

  • Concept
  • Characterization: volume, velocity, variety, value
  • Fundamental capability and use cases
  • Industry movements and major players

Lab 1: Business Case

Day 1 - Afternoon

Lifecycle Model for Strategization and Operationalization

  • End-to-end lifespan
  • Suitability assessment
  • Adoption strategy and maturity blueprint
  • Phased roadmap

Lab 2: Roadmapping

Day 2 - Morning

NoSQL Landscape and Taxonomy

  • CAP Theorem
  • Repository classification
  • Pros/cons comparison and selection criteria
  • Convergence and tradeoff analysis

Lab 3: NoSQL Selection

Day 2 - Afternoon

Reference Architecture and Platform Stack

  • Building blocks
  • Framework
  • Integration mechanism
  • Scale-out options and quality of services

Lab 4: Architecture Conceptualization

Day 3 - Morning

Basic Methods for Solution Analysis and Design

  • Data ingestion and bulk loading
  • Data reporting and visualization
  • Schema design and performance tweak
  • MadReduce programming

Lab 5: Usage Patterns and MapReduce

Day 3 - Afternoon

Advanced Methods for Solution Development and Implementation

  • Design patterns
  • Streaming and real-time enabling
  • Compaction and aggregation
  • Search: Solr, ElasticSearch

Lab 6: Real-time Solution and Search