MCALA Div. of MindMap IT Solution (P) Ltd.

TM

Big Data Analytics For BusinessBig Data Analytics For Business

• 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

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.

Big Data Analytics – Why?

TM

Why MCAL ?

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

About this course:

By completing 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.

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:

Course Variants

Course Delivery

In-depth variant will consist of:

=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

= 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

Method: Classroom Contact Program.

= Theory sessions

= Hands-on sessions

= Case Study and Analysis sessions

Data Processing

Modern Database Concepts:

Introduction to MapReduce:

Hadoop Hands-on:

4Data processing over the years4New data generation agents4Inadequacy of relational database systems4Nature of queries - Earlier planned, now dynamic4Examples of queries that need to be answered now4Solutions - New database trends (Columnar databases)4Solutions - New data processing methods (Map Reduce)4Case studies: Technology companies4Case studies: Other companies

4Relational databases and their limitations4How to solve the problem of flexible schema - Key/Value method of data storage4Advantages of Key / value method of storage & limitations4How does this provide schema flexibility?4How does this support efficient data storage?4How does this support distributed data storage?4How does it provide fault tolerance?4How does it ensure speed of query?4How is it capable of answering conventional database queries?4Overview of some columnar databases: MongoDB, Dynamo, Hbase4Who uses these databases?4Store now, process later philosophy; and how to go about it?

4What is MapReduce and the need for it.4Real Life Examples of Map Reduce in action4Evolution of MapReduce technique4Decomposition of some frequent tasks into MapReduce4How MapReduce can be used to perform database tasks4Map Reduce: Inputs and Outputs; files and programs4How is Map Reduce implemented in real life? Architecture of MapReduce system.4Introduction to Hadoop and overview

4Introduction to AWS4Introduction to EMR: Inputs and outputs4Running the wordcount example4Analysis of inputs and outputs

COURSE COVERAGE:

Hadoop:

Hadoop Distributions:

Hadoop Installation:

Hadoop Ecosystem:

Business Analytics:

Application:

4Getting deeper into Hadoop architecture4HDFS4Stages of Hadoop Mapreduce4Hadoop interfaces4Hadoop Ecosystem - An introduction46-Hadoop installation and Configuration4Cygwin4SSH

4Hadoop distributables - and introduction4Extraction4Directory walk-through4Documentation walk-through4Identification of important files / configuration elements

4Hadoop installation: Step-by-step4Hadoop Configuration4Hadoop Administration4Hadoop: Programmer's view

4Hive4Hbase4Pig4Sqoop4Avro

4Introduction to Analysis and Analytics4Business Statistics4Descriptive / Predictive / Prescriptive Statistics4Big Data Analytics4Trends in Analytics

4Project – Introduction4Solving the problems using MapReduce / Hadoop: An example4Project presentation4Problem identification and discussion4Solution + presentation preparation4Presentation + discussion