Big Data detail syllabus for Information Technology, effective from 2019-2020, is collected from BTEUP 2017 Syllabus official website and presented for diploma students. PDF download is possible from official site but you can download the istudy mobile app for syllabus on mobile. The course details such as exam duration, Teaching Hr/week, Practical Hr/week, Total Marks, internal marks, theory marks, duration and credits do visit complete sem subjects post given below.
For all other bteup syllabus 6th sem information tech 2019-2020 you can visit BTEUP Syllabus 6th Sem Information Tech 2019-2020 Subjects. For all other elective subjects do refer to Electives. The detail syllabus for big data is as follows.
Rationale:
Business data subject provides an introduction to Big data and analytics,which include the use of data, statistical and quantitative analysis, exploratory andpredictive models, to inform decisions and actions related to data.
Learning Outcomes:
After undergoing this course, the students will be able to:
- To explore the fundamental concepts of big data analytics
- To develop in-depth knowledge and understanding of the big data analyticdomain.
- To learn to analyse the big data using intelligent techniques.
- To understand the various search methods and visualization techniques.
- To learn to use various techniques for mining data stream.
- To understand the applications using Map Reduce Concepts
1. Introduction to Big Data & Hadoop: (18 Periods)
For complete syllabus and results, class timetable and more pls download iStudy. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.
2. Hadoop Architecture & Commands: (18 Periods)
- Hadoop 2.x Cluster Architecture
- Federation and High Availability Architecture
- Typical Production Hadoop Cluster
- Hadoop Cluster Modes
- Common Hadoop Shell Commands
- Hadoop 2.x Configuration Files
- Single Node Cluster & Multi-Node Cluster set up
- Basic Hadoop Administration
3. MapReduce: (18 Periods)
- Traditional way vs MapReduce way
- Why MapReduce
- YARN(Yet Another Resource Negotiator) Components
- YARN Architecture
- YARN MapReduce Application Execution Flow
- YARN Workflow
- Anatomy of MapReduce Program
- Input Splits, Relation between Input Splits and HDFS Blocks
- MapReduce: Combiner &Partitioner
4. Features of MapReduce (15 Periods)
For complete syllabus and results, class timetable and more pls download iStudy. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.
5. Project Work: (15 Periods)
List of Experiments:
- Write a very simple Hadoop program that counts the number of occurrences of each word in a text file.
- Suppose we use an input file that contains the following text:
- Write a Hadoop program to take a text file as input now convert all characters in upper case and save into another text file.
- Write a Hadoop program to take a text file as input now search a word in the file and count number of occurrence of that word in the file.
- Write a Hadoop program to take a text file as input now search a word in the file now replace that word with another word.
Don’t judge a book by its cover
Don’t put off until tomorrow what you can do today
Hope for the best, prepare for the worst
Projects:
For complete syllabus and results, class timetable and more pls download iStudy. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.
Instructional Strategy:
The subject is totally practical based. Students should be given clear idea about the basic concepts of programming related to Big Data.
Means of Assessment:
- Assignments and quiz/class tests, mid-term and end-term written tests
- Actual laboratory and practical work, exercises and viva-voce
- Software installation, operation, development and viva-voce
Text Books:
- Big Data Analytics with R and Hadoop by Vignesh Prajapati
- Data Science for Business: What You Need to Know about Data Miningby om Fawcett
- Hadoop for Dummies by Dirk Deroos
- The Human Face of Big Data by Rick Smolan and Jennifer Erwitt
- Big Data: A Revolution That Will Transform How We Live, Work, and Think by Kenneth Cukier and Viktor Mayer-Schonberger
- Hadoop – The Definitive Guide by Tom White
- e-books/e-tools/relevant software to be used as recommended by AICTE/UPBTE/NITTTR, Chandigarh.
Reference Books:
- http://swavam. gov.in
- http://spoken-tutorial.org
For detail syllabus of all other subjects of BE Information Tech, 2019-2020 scheme do visit Information Tech 6 syllabus for 2019-2020 Scheme.
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