Big Data and Hadoop Training batch in Pune is scheduled to commence on December 7th, 2013.This batch will be as per a new revamped four day schedule, contents and focus, based on feedback from participants of earlier courses. The training is conducted in a workshop like environment with an effective blend of hands-on practicals and assignments to augment the fundamental theory covered. About the Faculty: He is a Doctorate in Engineering and an industry veteran with more than twenty five years experience in launching new technologies, products and businesses. He has been involved in acquiring five patents for the company that he has worked for. Big Data Analytics – Why? Data is now generated by more sources and at ever increasing rates. Examples include Social Media sites, GPS based tracking systems, point of sale equipment, etc. The ability to process such data can provide that essential edge required for business success. Demand for Big Data professionals is rapidly increasing. Knowledge of Big Data can provide an advantage leading to faster professional advancement About this course This course on Big Data Analytics for Business is a combination of essential fundamentals, practical techniques, hands-on sessions on Hadoop, and case studies to cement all this together. By completing this course you will be able to …  Understand fundamentals of analytics: Descriptive, Predictive and Prescriptive Analytics  Know what ‘Big Data’, Map Reduce and Hadoop are all about  Get a grip on the structure of Big Data applications  Effectively use Big Data techniques like Map Reduce and tools like Hadoop, Hive, Hbase, Pig  Choose the most appropriate tools to solve Big Data problems  Identify, propose and lead Big Data projects in your organizations Course Content -  What is Big Data?  Overview of Big Data tools and techniques  In-depth coverage of Map-reduce techniques to manage Big Data  Hadoop - In Depth  HDFS – In Depth  Installing and managing Hadoop – Hands-on  Introduction to Hadoop Clusters  Hands-on session using native installation and Amazon EMR implementation of Hadoop  The Hadoop ecosystem: Pig, HIVE, HBase, Pig, SQOOP and Flume  Analytics: Descriptive, Predictive and Prescriptive  What is Big Data Analytics  Introducing Analytics in the enterprise: Case Studies  Trends in Big Data Analytics The course takes a "hands-on" approach to ensure that the basics are understood very well and assimilated concepts are applied in practice. Essential pre-requisite for practitioner course: Java programming language. Note: Basic Java Module for participants those who are new to Java.

1. TM
MCAL
A Div. of MindMap IT Solution (P) Ltd.
Big Data Analytics For Business

2. Big Data Analytics – Why?
• Data is now generated by more sources and at
ever increasing rates
• Examples include Social Media sites, GPS
based tracking systems, point of sale
equipment, etc.
• The ability to process such data can provide
that essential edge required for business
success
• Demand for Big Data professionals is rapidly
increasing
• Knowledge of Big Data can provide an
advantage leading to faster professional
advancement
With increasing complexities of business decisions, CxOs are seeking active tools and dashboards that will
help them in planning, forecasting, and budgeting for rapid business growth. Big Data analytics has already
become an important tool in their arsenal to achieve these objectives. MCAL’s Big Data Analytics for
Business program helps you launch yourself with excellent exposure to Big Data techniques and tools
TM
Why MCAL ?
TM
MCAL (Management Consulting & Advanced Learnings) is the leading high-end consulting and training company in
South Asia having expertise in the areas like Business Analysis, Management Consulting, Project Management , Sales,
Finance, Cloud Computing, Six Sigma, Android, Big Data, Data Analytic IT Service Management / ITIL framework.
We are serving most of the fortune 500 companies present in India. In the last 5 years, we helped more than 5000
professionals have shaped their career with accelerated growth.
Our exceptional track record and innovative approach make us one of most liked Training and Consulting Partner for
our clients, from Individuals to MNCs.
We are associated and approved from by the Global Bodies like IIBA -Canada, PMI -US, TUV -Germany, IREB ®
Germany and ITIL -UK, this is a unique achievement for any Indian Company.
®
®
®
®

3. About this course:
This course on Big Data Analytics for Business is a
combination of essential fundamentals, practical
techniques, hands-on sessions on Hadoop, and
case studies to cement all this together.
By completing this course:
Understand fundamentals of analytics
Know what‘Big Data’ analytics is all about
Get a grip on Big Data applications
Identify problem areas that can be tackled by Big
Data analytics
Effectively Use Big Data tools like Hadoop
Choose the most appropriate tools to solve Big Data
problems
Propose and lead Big Data related projects in your
organizations
Who Should Attend:
=
Managers
and Executives who wish to
harness the power of business analytics to
sharpen their decision making process.
=
Experienced professionals who wish to get
well rounded insights into business analytics
and its applications.
=
Graduates who wish to build & pursue career
in business analytics
Course Variants
=
For Executives
(CXOs and Managers): One
day intensive course
=
For practitioners and students: Five day
in depth course
Note: Customized corporate programs can also
be scheduled as per requirements
Course Delivery
Method: Classroom Contact Program.
In-depth variant will consist of:
=
Theory
sessions
=
Hands-on
sessions
=
Case Study
and Analysis sessions
COURSE COVERAGE:
Data Processing
4
Data processing over the years
4
New data generation agents
4of relational database systems
Inadequacy
4
Nature of queries - Earlier planned, now dynamic
4 queries that need to be answered now
Examples of
4
Solutions - New database trends (Columnar databases)
4
Solutions - New data processing methods (Map Reduce)
4 Technology companies
Case studies:
4 Other companies
Case studies:
Modern Database Concepts:
4
Relational databases and their limitations
4 the problem of flexible schema - Key/Value method of data storage
How to solve
4of Key / value method of storage & limitations
Advantages
4 provide schema flexibility?
How does this
4 support efficient data storage?
How does this
4 support distributed data storage?
How does this
4 provide fault tolerance?
How does it
4 ensure speed of query?
How does it
4
How is it capable of answering conventional database queries?
4 some columnar databases: MongoDB, Dynamo, Hbase
Overview of
4
Who uses these databases?
4
Store now, process later philosophy; and how to go about it?
Introduction to MapReduce:
4
What is MapReduce and the need for it.
4
Real Life Examples of Map Reduce in action
4 MapReduce technique
Evolution of
4 of some frequent tasks into MapReduce
Decomposition
4
How MapReduce can be used to perform database tasks
4 Inputs and Outputs; files and programs
Map Reduce:
4Reduce implemented in real life? Architecture of MapReduce system.
How is Map
4 to Hadoop and overview
Introduction
Hadoop Hands-on:
4 to AWS
Introduction
4 to EMR: Inputs and outputs
Introduction
4 wordcount example
Running the
4
Analysis of inputs and outputs
Hadoop:
4 into Hadoop architecture
Getting deeper
4
HDFS
4
Stages of Hadoop Mapreduce
4
Hadoop interfaces
4
Hadoop Ecosystem - An introduction
4
6-Hadoop installation and Configuration
4
Cygwin
4
SSH
Hadoop Distributions:
4
Hadoop distributables - and introduction
4
Extraction
4
Directory walk-through
4
Documentation walk-through
4 of important files / configuration elements
Identification
Hadoop Installation:
4
Hadoop installation: Step-by-step
4
Hadoop Configuration
4
Hadoop Administration
4
Hadoop: Programmer's view
Hadoop Ecosystem:
4
Hive
4
Hbase
4
Pig
4
Sqoop
4
Avro
Business Analytics:
4 to Analysis and Analytics
Introduction
4
Business Statistics
4 Predictive / Prescriptive Statistics
Descriptive /
4
Big Data Analytics
4
Trends in Analytics
Application:
4
Project – Introduction
4
Solving the problems using MapReduce / Hadoop: An example
4
Project presentation
4
Problem identification and discussion
4
Solution + presentation preparation
4 + discussion
Presentation