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Big Data Fundamentals: Concepts, Drivers & Techniques

PART I: The Fundamentals of Big Data
Chapter 1: Understanding Big Data

Concepts and Terminology
Datasets
Data Analysis
Data Analytics
Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
Business Intelligence (BI)
Key Performance Indicators (KPI)
Big Data Characteristics
Volume
Velocity
Variety
Veracity
Value
Different Types of Data
Structured Data
Unstructured Data
Semi-structured Data
Metadata
Case Study Background
History
Technical Infrastructure and Automation Environment
Business Goals and Obstacles
Case Study Example
Identifying Data Characteristics
Volume
Velocity
Variety
Veracity
Value
Identifying Types of Data

Chapter 2: Business Motivations and Drivers for Big Data Adoption

Marketplace Dynamics
Business Architecture
Business Process Management
Information and Communications Technology
Data Analytics and Data Science
Digitization
Affordable Technology and Commodity Hardware
Social Media
Hyper-Connected Communities and Devices
Cloud Computing
Internet of Everything (IoE)
Case Study Example

Chapter 3: Big Data Adoption and Planning

Considerations
Organization Prerequisites
Data Procurement
Privacy
Security
Provenance
Limited Realtime Support
Distinct Performance Challenges
Distinct Governance Requirements
Distinct Methodology
Clouds
Big Data Analytics Lifecycle
Business Case Evaluation
Data Identification
Data Acquisition and Filtering
Data Extraction
Data Validation and Cleansing
Data Aggregation and Representation
Data Analysis
Data Visualization
Utilization of Analysis Results
Case Study Example
Big Data Analytics Lifecycle
Business Case Evaluation
Data Identification
Data Acquisition and Filtering
Data Extraction
Data Validation and Cleansing
Data Aggregation and Representation
Data Analysis
Data Visualization
Utilization of Analysis Results

Chapter 4: Enterprise Technologies and Big Data Business Intelligence

Online Transaction Processing (OLTP)
Online Analytical Processing (OLAP)
Extract Transform Load (ETL)
Data Warehouses
Data Marts
Traditional BI
Ad-hoc Reports
Dashboards
Big Data BI
Traditional Data Visualization
Data Visualization for Big Data
Case Study Example
Enterprise Technology
Big Data Business Intelligence

PART II: Storing and Analyzing Big Data
Chapter 5: Big Data Storage Concepts

Clusters
File Systems and Distributed File Systems
NoSQL
Sharding
Replication
Master-Slave
Peer-to-Peer
Sharding and Replication
Combining Sharding and Master-Slave Replication
Combining Sharding and Peer-to-Peer Replication
CAP Theorem
ACID
BASE
Case Study Example

Chapter 6: Big Data Processing Concepts

Parallel Data Processing
Distributed Data Processing
Hadoop
Processing Workloads
Batch
Transactional
Cluster
Processing in Batch Mode
Batch Processing with MapReduce
Map and Reduce Tasks
Map
Combine
Partition9
Shuffle and Sort
Reduce
A Simple MapReduce Example
Understanding MapReduce Algorithms
Processing in Realtime Mode
Speed Consistency Volume (SCV)
Event Stream Processing
Complex Event Processing
Realtime Big Data Processing and SCV
Realtime Big Data Processing and MapReduce
Case Study Example
Processing Workloads
Processing in Batch Mode
Processing in Realtime

Chapter 7: Big Data Storage Technology

On-Disk Storage Devices
Distributed File Systems
RDBMS Databases
NoSQL Databases
Characteristics
Rationale
Types
Key-Value
Document
Column-Family
Graph
NewSQL Databases
In-Memory Storage Devices
In-Memory Data Grids
Read-through
Write-through
Write-behind
Refresh-ahead
In-Memory Databases
Case Study Example

Chapter 8: Big Data Analysis Techniques

Quantitative Analysis
Qualitative Analysis
Data Mining
Statistical Analysis
A/B Testing
Correlation
Regression
Machine Learning
Classification (Supervised Machine Learning)
Clustering (Unsupervised Machine Learning)
Outlier Detection
Filtering
Semantic Analysis
Natural Language Processing
Text Analytics
Sentiment Analysis
Visual Analysis Techniques
Heat Maps
Time Series Plots
Network Graphs
Spatial Data Mapping
Case Study Example
Correlation
Regression
Time Series Plot
Clustering
Classification

Appendix A: Case Study Conclusion
About the Authors
Index
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