CS8091 Big Data Analytics
CS8091 Big Data Analytics MCQ Multi Choice Questions, Lecture Notes, Books, Study Materials, Question Papers, Syllabus Part-A 2 marks with answers CS8091 Big Data Analytics MCQ Multi Choice Questions, Subjects Important Part-B 16 marks Questions, PDF Books, Question Bank with answers Key And MCQ Question & Answer, Unit Wise Important Question And Answers, One Mark Question With Answers, Choose The Best Answer.
Download link is provided for Students to download the Anna University CS8091 Big Data Analytics MCQ Multi Choice Questions, Lecture Notes, Books, Study Materials, Question Papers, Syllabus Part A 2 marks with answers & Part B 16 marks Question, Question Bank with answers, MCQ Question & Answer, Unit Wise Important Question And Answers, One Mark Question With Answers, Choose The Best Answer. All the materials are listed below for the students to make use of it and score good (maximum) marks with our study materials.
Subject Details
| SEMESTER : | 07 |
| SUBJECT CODE : | CS8091 |
| SUBJECT NAME : | Big Data Analytics |
| DEPARTMENT : | Computer Science and Engineering (CSE) |
| YEAR : | Final Year (IV Year) |
| REGULATION : | 2017 |
| CONTENT : | Syllabus, Lecture Notes, Important Part-A 2 Marks Questions and Important Part-B 13 & Part-C 15 Mark Questions, Previous Years Question Papers Collections and Question Banks. |
| FORMAT: |
“CS8091 Big Data Analytics Notes, Lecture Notes Previous Years Question Papers”
“CS8091 Big Data Analytics Important 13 marks Questions with Answers”
“CS8091 Big Data Analytics Important 15 marks Questions with Answers”
“CS8091 Big Data Analytics Important 2 marks Questions with Answers”
“CS8091 Big Data Analytics Important Part A, Part B & Part C Questions”
“CS8091 Big Data Analytics Syllabus, Local Author Books, Question Banks”
CS8091 Big Data Analytics MCQ Multi Choice Questions, Lecture Notes & Part-A, Part-B & Part-C Important Questions with Answers
Syllabus
CS8091 Big Data Analytics
UNIT I INTRODUCTION TO BIG DATA
Evolution of Big data Best Practices for Big data Analytics Big data characteristics Validating The Promotion of the Value of Big Data Big Data Use Cases- Characteristics of Big Data Applications Perception and Quantification of Value -Understanding Big Data Storage A General Overview of High-Performance Architecture HDFS MapReduce and YARN Map Reduce Programming Model
UNIT II CLUSTERING AND CLASSIFICATION
Advanced Analytical Theory and Methods: Overview of Clustering K-means Use Cases Overview of the Method Determining the Number of Clusters Diagnostics Reasons to Choose and Cautions .- Classification: Decision Trees Overview of a Decision Tree The General Algorithm Decision Tree Algorithms Evaluating a Decision Tree Decision Trees in R Naïve Bayes Bayes Theorem Naïve Bayes Classifier.
UNIT III ASSOCIATION AND RECOMMENDATION SYSTEM
Advanced Analytical Theory and Methods: Association Rules Overview Apriori Algorithm Evaluation of Candidate Rules Applications of Association Rules Finding Association& finding similarity Recommendation System: Collaborative Recommendation- Content Based Recommendation Knowledge Based Recommendation- Hybrid Recommendation Approaches.
UNIT IV STREAM MEMORY
Introduction to Streams Concepts Stream Data Model and Architecture Stream Computing,
Sampling Data in a Stream Filtering Streams Counting Distinct Elements in a Stream Estimating
moments Counting oneness in a Window Decaying Window Real time Analytics Platform(RTAP) applications Case Studies Real Time Sentiment Analysis, Stock Market Predictions. Using Graph Analytics for Big Data: Graph Analytics
UNIT V NOSQL DATA MANAGEMENT FOR BIG DATA AND VISUALIZATION
NoSQL Databases : Schema-less Models?: Increasing Flexibility for Data Manipulation-Key Value Stores- Document Stores Tabular Stores Object Data Stores Graph Databases Hive Sharding -
Hbase Analyzing big data with twitter Big data for E-Commerce Big data for blogs Review of Basic Data Analytic Methods using R.
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CS8091 Big Data Analytics MCQ Collection
CS8091 MCQ Collection 01 – DOWNLOAD
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