Contents

1. Introduction to Big Data

1. Introduction

2. Big Data Taxonomy

3. Sources of Big Data

4. Need for Hadoop

5. Varying Data Structure

6. 3V's of Big Data/Characteristics of Big Data

7. Applications of Big Data

8. Challenges in Big Data

9. Big Data Implications for Industries 

2. Emerging Database Landscape

1. Introduction

2. The Scale out Architecture

3. Database Workload and its Characteristics

4. Implications of Big Data Scale on Data Processing 

3. Application Architecture and Data Modeling for Big Data and Analytics

1. Big Data Warehouse and Analysis

2. Big Data Warehouse System Requirements and Hybrid Architectures

3. Enterprise Data Platform Ecosystem

4. Big Data and Master Data Management (MDM)

5. Understanding Data Integration Pattern

6. Big Data Workload Design Approaches

7. Map Reduce Pattern, Algorithms and Use Cases 

4. The Hadoop Ecosystem

1. Introduction

2. Hadoop Architecture

3. YARN Framework

4. History of Hadoop – Facebook, Dynamo, Yahoo, Google

5. Hadoop Components – HDFS, Map Reduce

6. Introduction to Pig, Hive, HBase, Mahout

7. Mahout Installation of Single Node Cluster Installation of Java Hadoop Configuration 

5. Extracting Value from Big Data

1. Introduction

2. In Memory Data Grid for Real Time Analysis

3. MapReduce and Real Time Processing, Use Cases 

6. Big Data Analytics Methodology

1. Big Data Analytics Methodology – Analyze and Evaluate Business Cases

2. Develop Business Hypothesis