(Ebook) Big data analytics 1st Edition by Vijayalakshmi Radha Shankarmani ISBN 9788126558650 8126558652

(Ebook) Big data analytics 1st Edition by Vijayalakshmi Radha Shankarmani ISBN 9788126558650 8126558652

(Ebook) Big data analytics 1st Edition by Vijayalakshmi Radha Shankarmani - Ebook PDF Instant Download/Delivery: 9788126558650 ,8126558652
Full download (Ebook) Big data analytics 1st Edition after payment

Product details:

ISBN 10: 8126558652
ISBN 13: 9788126558650
Author: Vijayalakshmi Radha Shankarmani

(Ebook) Big data analytics 1st Edition Table of contents:

Chapter 1: Big Data Analytics

• Learning Objectives

• Introduction to Big Data

• Big Data Characteristics

• Types of Big Data

• Traditional vs. Big Data Approach

• Technologies Available for Big Data

• Infrastructure for Big Data

• Use of Data Analytics

• Big Data Challenges

• Desired Properties of a Big Data System

• Case Study of Big Data Solutions

Chapter 2: Hadoop

• Introduction

• What is Hadoop?

• Core Hadoop Components

• Hadoop Ecosystem

• Hive

• Physical Architecture

• Hadoop Limitations

Chapter 3: What is NoSQL?

• What is NoSQL?

• NoSQL Business Drivers

• NoSQL Case Studies

• NoSQL Data Architectural Patterns

• Variations of NoSQL Architectural Patterns

• Using NoSQL to Manage Big Data

Chapter 4: MapReduce

• MapReduce and the New Software Stack

• MapReduce

• Algorithms Using MapReduce

Chapter 5: Finding Similar Items

• Introduction

• Nearest Neighbor Search

• Applications of Nearest Neighbor Search

• Similarity of Documents

• Collaborative Filtering as a Similar‑Sets Problem

• Recommendation Based on User Ratings

• Distance Measures

Chapter 6: Mining Data Streams

• Introduction

• Data Stream Management Systems

• Data Stream Mining

• Examples of Data Stream Applications

• Stream Queries

• Issues in Data Stream Query Processing

• Sampling in Data Streams

• Filtering Streams

• Querying on Windows & Decaying Windows

Chapter 7: Link Analysis

• Introduction

• History of Search Engines and Spam

• PageRank

• Efficient Computation of PageRank

• Topic‑Sensitive PageRank

• Link Spam

• Hubs and Authorities

Chapter 8: Frequent Itemset Mining

• Introduction

• Market‑Basket Model

• Algorithm for Finding Frequent Itemsets

• Handling Larger Datasets in Memory

• Limited Pass Algorithms

• Counting Frequent Items in a Stream

Chapter 9: Clustering Approaches

• Introduction

• Overview of Clustering Techniques

• Hierarchical Clustering

• Partitioning Methods

• The CURE Algorithm

• Clustering Streams

Chapter 10: Recommendation Systems

• Introduction

• A Model for Recommendation Systems

• Collaborative‑Filtering System

• Content‑Based Recommendations

Chapter 11: Mining Social Network Graphs

• Introduction

• Applications of Social Network Mining

• Social Networks as a Graph

• Types of Social Networks

• Clustering of Social Graphs

• Direct Discovery of Communities

• SimRank

• Counting Triangles in a Social Graph

• Summary

• Exercises

• Programming Assignments

• References

• Appendix

• Index

People also search for (Ebook) Big data analytics 1st Edition:

big data analytics using pyspark
    
use of big data analytics
    
unstructured data in big data analytics
    
ucf big data analytics phd
    
understanding the pros and cons of big data analytics

Tags: Vijayalakshmi Radha Shankarmani, Big data analytics