Objectives

This intensive training course aims at making students cognisant of NoSQL systems capabilities and how they can be leveraged.

The course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the learned material and make them confident in applying the acquired knowledge in practice.

Topics

  • Defining Big Data
  • Big Data Stores Overview
  • NoSQL
  • Big Data Business Intelligence and Analytics
  • Google App Engine Interfaces
  • Working with MongoDB

Audience

Technical leads and application developers

Pre-requisites

Participants should be familiar with programming in Java and using Eclipse development environment

Duration

2 days

Outline for Big Data and NoSQL for Developers

1. Defining Big Data

  • Transforming Data into Business Information
  • Definition of Big Data
  • Challenges Posed by Big Data
  • The Cloud and Big Data
  • The Business Value of Big Data
  • Big Data: Hype or Reality?

2. Big Data Systems Overview

  • Limitations of Relational Databases
  • NoSQL Database Systems
  • The CAP theorem
  • Limitations of NoSQL Databases
  • Big Data Sharding
  • Amazon S3
  • Amazon S3 Security
  • Data Lifecycle Management with Amazon S3
  • Amazon S3 Cost Monitoring
  • Google BigTable
  • BigTable Design
  • Google App Engine
  • App Engine Billing
  • Hadoop
  • Hadoop Core Components
  • Hadoop Distributed File System
  • HBase
  • HBase Design
  • Cassandra
  • Neo4J
  • MemcacheDB
  • MongoDB
  • MongoDB Operational Intelligence
  • MongoDB Use Cases

3. Big Data Business Intelligence and Analytics

  • Comparison with Other Systems
  • NoSQL Data Querying and Processing
  • MapReduce Framework
  • Analyzing Big Data with Hadoop
  • Making things simpler with Pig Latin
  • Example of a Pig Script in Batch Mode
  • Amazon Elastic  MapReduce
  • Business Analytics with Hive
  • The UnQL Specification

4. Working with Google App Engine

  • Runtime Environments
  • Development Environment
  • Big Data in Google App Engine
  • App Engine Datastore
  • Google Cloud SQL
  • Google Cloud Storage
  • Blobstore
  • Java  Data Store API
  • App Engine Services
  • App Identity
  • Memcache
  • OAuth
  • Task Queues
  • URL Fetch
  • XMPP

5. Working with MongoDB

  • Drivers and Client Libraries
  • MongoDB Data Model
  • Administration Console
  • Security and Authentication
  • Data import and Export
  • Managing MongoDB Lifecycles
  • Read Operations
  • Cursors
  • Write Operations
  • Querying, Limiting, Sorting and Aggregating data
  • MongoDB QL
  • Optimizing Queries with Indexes