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Contact information:
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NAGPUR
Mobile: 9595 321479
               90281 57794
Tel: 0712-2557946

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Tel: 0712-2701833
Email: atlantaworld@gmail.com
www.atlantacomputer.in

University Syllabus Course and Classes For MCM Big Data & Hadoop

Atlanta Computer Institute Nagpur conducts Tuition Classes forMCMFirst Year (  Part 1 ) , MCM Second Year (   Part 2  ) for all universities in India . The Following syllabus is of Nagpur University.  Final Year Projects Training is also given to  MCM Students.
Big Data & Hadoop MCM semester 4

Paper - III: Elective Foundation


Elective Foundation - I: Big Data & Hadoop




UNIT - I
Types of Digital Data - Classification of Digital Data. Introduction to Big Data -Characteristics of Data, Evolution of Big Data, Definition of Big Data, Challenges with Big Data, What is Big Data?, Other Characteristics of Data Which are not Definitional Traits of Big Data, Why Big Data?, Are We Just an Information Consumer or Do we also Produce Information?, Traditional Business Intelligence (BI) versus Big Data, A Typical Data Warehouse Environment, A Typical Hadoop Environment, What is New Today?, What is changing in the Realms of Big Data?. Big Data Analytics - Where do we Begin?, What is Big Data Analytics?, What Big Data Analytics Isn‘t?, Why this Sudden Hype Around Big Data Analytics?, Classification of Analytics, Greatest Challenges that Prevent Businesses from Capitalizing on Big Data, Top Challenges Facing Big Data, Why is Big Data Analytics Important?, What Kind of Technologies are we looking Toward to Help Meet the Challenges Posed by Big Data?, Data Science, Data Scientist…Your New Best Friend!!!, Terminologies Used in Big Data Environments, Basically Available Soft State Eventual Consistency (BASE), Few Top Analytics Tools.

UNIT - II
The Big Data Technology Landscape - NoSQL (Not Only SQL), Hadoop. Introduction to Hadoop - Introducing Hadoop, Why Hadoop?, Why not RDBMS?, RDBMS versus Hadoop, Distributed Computing Challenges, History of Hadoop, Hadoop Overview, Use Case of Hadoop, Hadoop Distributors, HDFS (Hadoop Distributed File System), Processing Data with Hadoop, Managing Resources and Applications with Hadoop
YARN (Yet another Resource Negotiator), Interacting with Hadoop Ecosystem. Introduction to MongoDB - What is MongoDB?, Why MongoDB?, Terms Used in RDBMS and MongoDB, Data Types in MongoDB, MongoDB Query Language.

UNIT - III
Introduction to Cassandra - Apache Cassandra - An Introduction, Features of Cassandra, CQL Data Types, CQLSH, Keyspaces, CRUD (Create, Read, Update and Delete) Operations, Collections, Using a Counter, Time to Live (TTL), Alter Commands, Import and Export, Querying System Tables, Practice Examples. Introduction to MAPREDUCE Programming - Introduction, Mapper, Reducer, Combiner, Partitioner, Searching, Sorting, Compression. Introduction to Hive - What is Hive?, Hive Architecture, Hive Data Types, Hive File Format, Hive Query Language (HQL), RCFile Implementation, SerDe, User-Defined Function (UDF).

UNIT - IV
Introduction to Pig - What is Pig?, The Anatomy of Pig, Pig on Hadoop, Pig Philosophy, Use Case for Pig: ETL Processing, Pig Latin Overview, Data Types in Pig, Running Pig 10.9 Execution Modes of Pig, HDFS Commands, Relational Operators, Eval Function, Complex Data Types, Piggy Bank, User-Defined Functions (UDF), Parameter Substitution, Diagnostic Operator, Word Count Example using Pig, When to use Pig?,

MCM Syllabus RTMNU
When not to use Pig?, Pig at Yahoo!, Pig versus Hive. Jasper Report using Jasper soft -
Introduction to Jasper Reports, Connecting to MongoDB NoSQL Database, Connecting to Cassandra NoSQL Database. Introduction to Machine Learning - Introduction to Machine Learning, Machine Learning Algorithms.


Text Book:
1. Seema Acharya & Subhashini Chellappan, Big data and Analytics, Wiley.
Reference Books:
1. Radha Shankarmani & M. Vijayalakshmi, Big data Analytics, Wiley.
2. Chuck Lam, Hadoop in Action, Dreamtech Press.
3. Philip Kromer & Russell Jurney, Big Data for Chimps, Shroff Publishers, O‘Reilly.
4. Chandrakant Naikodi, Managing Big Data, Vikas publishing.
5. Chriss Eaton, Dirik Deroos, Tom Deutsch, George Lapis, Paul Zikopoulos,
Understanding Big Data, McGraw-Hill.

New MCM Syllabus Semester Pattern  From 2016 - 17

Theory

1.  Fundamental of Information Technology 

2.  Programming in C & OOPs Concept

3.  Introduction to Operating Systems 

4.  Computerized Accounting ( Tally ERP 9  ) 

Practical

1. Practical-I : Programming in C & Operating Systems

2. Practical-II : Tally ( ERP 9 ) & MS-Office 

MCM Semester 2

Theory

1.  Management Information Systems

2.   Core Java 

3.  Quantitative Techniques & Operation Research

4.  E-Commerce and Web Designing 

Practical

1. Practical-I : Core Java 

2. Practical-II : HTML, JavaScript 

MCM Part-II

MCM Semester 3

 (A) Theory

1.   Advanced Database Management System 

2. Principles & Techniques of Management

3.  Electives

               ( i )     PHP & My-SQL

              ( ii )     VB.Net 

              ( iii )     C#.Net                 

4.  Research Methodology

 (B) Practical

1. Practical-I : SQL & PL/SQL 

2. Practical-II : Electives 

MCM Semester 4

 (A) Theory

1.   ASP.Net 

2.    Electives : (i) Advanced Java

                            (ii) Android Programming

                            (iii) Python

3.  Electives :   ( i ) Big Data & Hadoop  

                             ( ii ) Software Engineering   

                            ( iii )Strategic Management

(B) Practical

1. Practical-I : ASP.Net 

2. Practical-II : Electives 

(C)  Project

1. PROJECT 

 

BCA Bachelor Of Computer Application, BCCA, Bachelor of Commerce & Computer Application BE IT/CS, Information technology/Computer Science MCA, Master of Computer Application MCM, Master of Computer Management Diploma , Polytechnic B.Arch Bachelor Of Architecture, Others,

Basic Programming

C / C++ ,

Testing

Software Testing,

Hardware & Networking

CCNA, MCSE, Hardware, Networking
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