Introduction to Big Data and NoSQL

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Course Description

We live in the information age where business success is grounded on the ability of organizations to convert raw data coming from various sources into high-grade business information.

Many organizations are overwhelmed by the sheer volume of information they have to process in order to stay competitive.  Traditional database systems may become either prohibitively expensive to handle the exponential growth of data volumes or found unsuitable for the job.  At this point, the data gets mystically morphed into the Big Data.

This Introduction to Big Data and NoSQL training course provides an introduction to Big Data as well as NoSQL (Not Only SQL) database systems.  The fundamental concepts of and ideas behind Big Data / NoSQL technologies are methodically explored and many buzzwords demystified.  The course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the subject.

Topics:

•     Defining Big Data
•     Big Data Stores Overview
•     NoSQL
•     Big Data Business Intelligence and Analytics
•     Real World Case Studies
•     Adopting NoSQL

Course Outline

Chapter 1. Defining Big Data

•     Transforming Data into Business Information
•     Quality of Data
•     Gartner's Definition of Big Data
•     More Definitions of Big Data
•     Processing Big Data
•     Challenges Posed by Big Data
•     The Cloud and Big Data
•     The Business Value of Big Data
•     Big Data: Hype or Reality?
•     Big Data Quiz
•     Big Data Quiz Answers

Chapter 2. NoSQL and Big Data Systems Overview

•     Limitations of Relational Databases
•     Limitations of Relational Databases (Cont'd)
•     What are NoSQL (Not Only SQL) Databases?
•     The Past and Present of the NoSQL World
•     NoSQL Database Properties
•     NoSQL Benefits
•     NoSQL Database Storage Types
•     The CAP Theorem
•     Mechanisms to Guarantee a Single CAP Property
•     NoSQL Systems CAP Triangle
•     Limitations of NoSQL Databases
•     Mix-and-match Approach
•     Big Data Sharding
•     Sharding Example
•     Amazon S3
•     Amazon Storage SLAs
•     Amazon Glacier
•     Amazon S3 Security
•     Data Lifecycle Management with Amazon S3
•     Amazon S3 Cost Monitoring
•     OpenStack
•     Object Store (Swift)
•     Components of Swift
•     Google BigTable
•     BigTable-based Applications
•     BigTable Design
•     Google Cloud Storage
•     Microsoft Azure
•     Hadoop
•     Hadoop Clusters
•     Hadoop's Core Components
•     Hadoop Distributed File System
•     Accessing HDFS
•     HBase
•     HBase Design
•     HBase Design
•     MemcacheDB
•     Using MemcacheDB instead of memcached
•     MongoDB
•     MongoDB (Cont'd)
•     MongoDB Operational Intelligence
•     MongoDB Use Cases
•     Apache Cassandra
•     Apache Cassandra Design
•     Cassandra's Main Features and Qualities of Service
•     Quiz
•     Quiz Answers

Chapter 3. Big Data Business Intelligence and Analytics

•     Traditional Business Intelligence and Analytics
•     OLAP Tasks
•     Data Mining Tasks
•     Big Data / NoSQL Solutions
•     NoSQL Data Querying and Processing
•     MapReduce Defined
•     MapReduce Explained
•     Example of Map & Reduce Operations using JavaScript
•     Hadoop
•     Hadoop-based Systems for Data Analysis
•     Hadoop's MapReduce
•     Hadoop's Streaming MapReduce
•     Streaming Use Cases
•     Setting up Java Classpath for Streaming Support
•     Making things simpler with Hadoop Pig Latin
•     Pig Latin Script Example
•     SQL Equivalent
•     What is Hive?
•     Hive Architecture
•     Interfacing with Hive
•     Hive Data Definition Language
•     Business Analytics with Hive
•     Amazon Elastic MapReduce
•     Big Data with Google App Engine (GAE)
•     GAE Dashboard
•     Example of Google AppEngine Java Datastore API
•     MongoDB Data Model
•     MongoDB Query Language (QL)
•     The
•     find
•     and
•     findOne
•     Methods
•     The
•     find
•     and
•     findOne
•     Methods
•     A MongoDB QL Example
•     The UnQL Specification
•     Quiz
•     Quiz Answers

Chapter 4. Big Data Real World Case Studies

•     Hadoop @ Yahoo
•     Yahoo for Hadoop
•     Yahoo!!
•     Big Data @ Facebook
•     Hive @ Facebook
•     Mailtrust (Rackspace's mail division)

Chapter 5. Adopting NoSQL

•     Hype Cycle and Technology Adoption Model
•     Barriers to Adoption
•     Dismantling Barriers to Adoption
•     Use Cases for NoSQL Database Systems
•     Example Applications
•     Industry trends
•     Enterprise Hadoop Solutions Offerings
•     Enterprise Big Data / NoSQL Offerings
•     IBM InfoSphere Platform
•     Oracle Big Data Appliance
•     NoSQL Technology Adoption Action Plan
•     Summary

Lab Exercises

    Lab 1. Using Object Storage in OpenStack
    Lab 2. Using MongoDB

Learning Path

• You are welcome to discuss which course is most suitable for you with a member of our team. Please contact us for further details.

Ways to Attend

• Attend a public course, if there is one available. Please check our schedule, or register your interest in joining a course in your area.
• Private onsite Team training also available, please contact us to discuss. We can customise this course to suit your business requirements.