ICGCIoT 2016 | 10-12 November 2016

Short Courses

The conference program includes short courses, which will be conducted by leading experts in the field. Details will get updated in the conference website and available in subsequent mailings. As of now we have the following short-courses confirmed:

Course 1: Introduction to Big Data & Analytics

Proposals for short courses can be submitted to chair@gciot-conference.org

Course 1
Full Day

Introduction to Big Data & Analytics

Course Leader

Ms. Revathy Padmanaban,
Big Data Architect, Consultant and Project Manager, OCBC Bank, Singapore

Date/Time

17 November 2017 (Friday) / 10.00 am to 6.00 pm

Fee

Rs. 1000 (local) / USD 50 (overseas)
(includes, Certificate, short course kit, buffet lunch & tea/coffee network session)

Who Should Attend

This course is designed for anyone who:

  • wants to understand big data landscape;
  • wants to analyze enormous amounts of data;
  • wants to work in Hadoop and its eco-system components, and
  • have a programming background and want to take career to next level.

Limited seats, on first-come first-serve basis.           

     

Course 1

Introduction to Big Data & Analytics

Course Leader

Ms. Revathy Padmanaban
Big Data Architect, Consultant and Project Manager, OCBC Bank, Singapore




Abstract
Big data is data that surpasses the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the limits of your database architectures. To process and get insights from this data, we must choose an alternative way to process it.The hot IT catchphrase, big data has become feasible as cost-effective approaches have now emerged to tame massive data. Within this data lies valuable information, previously hidden because of the amount of work required to extract them. To leading corporations, such as Walmart or Google, this power has been in reach for some time, but at fantastic cost. Today’s commodity hardware, cloud architectures and open source software bring big data processing into the reach of the less resourced. Big data processing is eminently feasible for even the small garage startups, who can cheaply rent server time in the cloud.The value of big data to an organization falls into two categories: analytical use and enabling new products. Big data analytics can reveal insights hidden previously by data too costly to process. The past decade’s successful web startups are prime examples of big data used as an enabler of new products and services. This short course will focus on the concept of big data technologies and business analytics with its strategic importance to any organization. Participants will be introduced to the concept of business analytics with big data technologies: Hadoop, Hive and HBase.


Course Outline

  1. Introduction to Big Data & Analytics
    • What is Big Data?
    • Characteristics of big data
    • Traditional data management systems and their limitations
    • Big Data Analytics
    • What is Hadoop?
    • Why is Hadoop used?
    • The Hadoop eco-system
    • Big Data/Hadoop use cases
  2. Hadoop - HDFS
    • HDFS Architecture
    • HDFS internals and use cases
    • HDFS Daemons
    • Basic Hadoop commands
    • Hands-on exercise
  3. Hive
    • Understanding Hive
    • Using Hive command line interface
    • Basic DDL operations
    • Hands-on examples
  4. HBase
    • HBase overview
    • HBase architecture
    • HBase data access
    • Overview of Zookeeper
    • Hands-on exercise

Who Should Attend

This course is designed for anyone who:

  • wants to understand big data landscape;
  • wants to analyze enormous amounts of data;
  • wants to work in Hadoop and its eco-system components, and
  • have a programming background and want to take career to next level.



Go to top of page