15IS61T: Big Data and Analytics Information Sci 6th Sem Syllabus for Diploma DTE Karnataka C15 Scheme

Big Data and Analytics detail DTE Kar Diploma syllabus for Information Science And Engineering (IS), C15 scheme is extracted from DTE Karnataka official website and presented for diploma students. The course code (15IS61T), and for 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. The syllabus PDFs can be downloaded from official website.

For all other information sci 6th sem syllabus for diploma c15 scheme dte karnataka you can visit Information Sci 6th Sem Syllabus for Diploma C15 Scheme DTE Karnataka Subjects. The detail syllabus for big data and analytics is as follows.

Pre-requisites:

Knowledge of programming language, database, queries.

Course Objectives:

1. Understand Big data concepts, applications.
2. Understanding the Big data Analytics, data science and data scientists.
3. Knowing the Hadoop concepts.
4. Knowledge of MongoDB.
5. Demonstrate R programming and data structure of R.
6. Implementation of loops,functions in R.

Course Outcomes:

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UNIT I :Data in connected world 10 Hrs

The Liberated data, Caged data, Big data is Big news, FERED, Search based Internet data, Survey data. Introduction to Big Data .Characteristics of Data. Evolution of big Data. Definition of Big data. Challenges with Big Data. What and why is Big Data. Traditional Business Intelligence versus Big Data. A Typical Data Warehouse Environment .What is changing in Realms of big Data?

UNIT II: Big Data Analytics 08 Hrs

Big Data Analytics. Classification of Analytics. Greatest Challenges that prevent businesses from capitalizing of Big Data. Importance of Big Data .Data science. Data scientist. Terminologies used in big Data Environments.

UNIT III: Introduction to Hadoop 06 Hrs

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UNIT IV:Introduction toMongoDB 12 Hrs

Introduction to MongoDB terms used in RDBMS MongoDB. Data Types .Query language in Mongo.

UNIT V:Introduction to R Programming 08 Hrs

Introduction to R Programming, R environment, Single -mode data structures,multi-mode data structures.

UNIT VI:Working with R Programming 08 Hrs

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Text Books:

1. Big Data and Analysis – Seema Acharya and Subhashni Chellappan, Wiley. (Chapters 2,3,4,6)
2. Practical Data Science with R -Hanning ,Dream tech Press.
3. Sams Teach Yourself R I 24 Hours, Andy Nicholls, RichardPugh, AimeeGott, Pearson Publication.
4. Getting Started with Data Science -Murtaza Haider,IBM Press.

Reference Books:

1. Analytics in Big Data World-Baesens, Wiley.
2. Big Data MBA-Schmaro.
3. Any other books covering the contents of the paper in more depth.
4. Latest and additional good books may be suggested and added from time to time.

SUGGESTED STUDENT ACTIVITIES:

Note: The following activities or similar activities for assessing CIE (IA) for 5 marks (Any one)

Student activity like mini-project, surveys, quizzes, etc. should be done in group of 1-2 students.

1. Each group should do any one of the following type activity or any other similar activity related to the course and before conduction, get it approved from concerned course coordinator and programme co-ordinator
2. Each group should conduct different activity and no repeating should occur.
1. Identify various fields where Big Data is used.
2. Recognize and Analyse the various softwares used for Big data analysis.
3. Conduct a survey on various applications ofBig data and submit a report of 3 to 4 pages.
4. Conduct a case study on any one Online Big data Processing System and submit a report of 3 to 4 pages.

Course Delivery:

The course will be delivered through Lectures and Power point presentations/ Video

Model Question Paper:

(CIE)

1. Define is Big data. List out the characteristics of data.
2. Discuss search based internet data.
3. Explain with a figure data science has multi-disciplinary.
4. Explain why big data analytics is important.

Model Question Paper:

PART-A

Answer any SIX questions. Each carries 5 marks.

1. Write the challenges with big data.
2. Discuss the big data analytics.
3. Define data science.
4. Explain the necessities of Hadoop.
5. Write the difference between RDBMS and Hadoop.
6. Explain aggregate function in MongoDB.
7. Write about the support for Dynamic Queries in MongoDB.
8. Illustrate the difference b/w an array and matrix in R.
9. Create a simple function in R. Write the conditions for naming a function.

PART-B

Answer any SEVEN full questions each carries 10 marks. 10X7=70 Marks

1. Explain coexistence of big data and data warehouse.
2. Explain the changing in the Realms of big data.
3. Explain with a figure data science has multi-disciplinary.
4. Write the high level architecture of HADOOP.
5. Illustrate the Cursors in MongoDB.
6. Explain the CRUD operations in MongoDB.
7. Define “list objects” .discuss how do we refer elements from a list in R.
8. Discuss why do we refer to vectors, matrices and arrays as “single mode structure in R.
9. Create a function that accept 2 input x and y and returns the value of x+y .
10. Write the difference between sapply and lapply.

For detail syllabus of all other subjects of BE Information Sci, C15 scheme do visit Information Sci 6th Sem syllabus for C15 scheme.

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