Big Data Analytics detailed syllabus for Master of Computer Applications (MCA), 2018 regulation has been taken from the University of Mumbai official website and presented for the MCA students. For Scheme related information like Course Code, Course Title, Test 1, Test 2, Avg, End Sem Exam, Team Work, Practical, Oral, Total, and other information, do visit full semester subjects post given below.
For Master of Computer Applications (MCA) 5th Sem scheme, 2018 regulation, do visit MCA 5th Sem 2018 Pattern Scheme. For the Elective-1 (Departmental Level) scheme of 5th Sem 2018 regulation (MCA), refer to MCA 5th Sem 2018 Pattern Elective-1 (Departmental Level) Scheme. The detailed syllabus for big data analytics is as follows.
MCADLE5041: Big Data Analytics Syllabus for MCA 5th Sem 2018 Pattern Mumbai University (Elective-1 (Departmental Level))
Prerequisites:
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Course Educational Objectives (CEO):
At the end of the course, the students will be able to
- Provide fundamental techniques and principles of Big Data Analytics
- Identify the tools required to manage and analyze Big Data
- Understand the data analytics techniques required to solve complex real world problems
Course Outcomes:
At the end of the course, the students will be able to:
- Develop and maintain reliable, scalable systems using Apache HADOOP
- Write Map Reduce based application
- Differentiate between conventional SQL and NoSQL
- Analyze and develop Big Data solutions using HIVE and PIG
1. Introduction
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2. Hadoop
Why Hadoop? Hadoop architecture, Hadoop components HDFS and YARN, comparison between YARN 1 and YARN 2 architecture, HDFS federation : Name Node, Data Node, Resource Manager, Job Tracker, Task Tracker Hadoop Ecosystem : Scoop, HIVE, PIG, Flume, Zookeeper, HBASE Hadoop installation in pseudo distribution mode, running HDFS commands 10
3. Map Reduce
Understanding Map Reduce, Map Task, Reduce Task, speculative execution, partioner and combiner in Map Reduce Running sample Map Reduce Program: Word Count. Algorithm using Map Reduce : -matrix vector multiplication, -grouping and aggregation -relational algebra operations 10
4. NoSQL
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5. HIVE
HIVE : background, architecture, warehouse directory and meta-store, HIVE query language, loading data into table, HIVE built-in functions, joins in HIVE, HIVE installation, HiveQL: querying data, sorting and aggregation 08
6. PIG
PIG : background, architecture, PIG Latin Basics, PIG execution modes, PIG processing – loading and transforming data, PIG built-in functions, filtering, grouping, sorting data Installation of PIG and PIG Latin commands 08
Reference Books:
For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
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Assessment:
Internal: Assessment consists of two tests (T1 and T2) .The final marks should be the average of the two tests. End Semester Theory Examination: Guidelines for setting up the question paper.
- Question paper will comprise of total six questions.
- Question Number One should be compulsory.
- All question carry equal marks.
- Students can attempt any three from the remaining.
- Questions will be mixed in nature (for example supposed Q.2 has part a from module 3 then part b will be from any module other than module 3).
In question paper weightage of each module will be proportional to number of respective lecture hours as mention in the syllabus.
For detail Syllabus of all subjects of MCA 5th Sem, 2018 regulation, visit MCA 5th Sem Subjects of 2018 Pattern.