With the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data. These huge volumes of data can be used for effective decision making and improved performance if analyzed properly. Due to its inherent characteristics, big data is very complex and cannot be handled and processed by traditional database management approaches. There is a need for sophisticated approaches, tools and technologies that can be used to store, manage and analyze these enormous amounts of data to make the best use of them.
Big Data Concepts, Technologies, and Applications covers the concepts, technologies, and applications of big data analytics. Presenting the state-of-the-art technologies in use for big data analytics. it provides an in-depth discussion about the important sectors where big data analytics has proven to be very effective in improving performance and helping industries to remain competitive. This book provides insight into the novel areas of big data analytics and the research directions for the scholars working in the domain. Highlights include:
The advantages, disadvantages and challenges of big data analytics
State-of-the-art technologies for big data analytics such as Hadoop, NoSQL databases, data lakes, deep learning and blockchain
The application of big data analytic in healthcare, business, social media analytics, fraud detection and prevention and governance
Exploring the concepts and technologies behind big data analytics, the book is an ideal resource for researchers, students, data scientists, data analysts and business analysts who need insight into big data analytics.
Section A. Understanding Big Data
Chapter 1. Overview of Big Data
Chapter 2. Challenges of Big Data
Chapter 3. Big Data Analytics
Section B. Big Data Technologies
Chapter 4. Hadoop Ecosystem
Chapter 5. NoSQL Databases
Chapter 6. Data Lakes
Chapter 7. Deep Learning
Chapter 8. Blockchain
Section C. Big Data Applications
Chapter 9. Big Data for Healthcare
Chapter 10. Big Data analytics for Fraud Detection and Prevention
Chapter 11. Big Data Analytics in Social Media
Chapter 12. Novel Applications and Research Directions in Big Data Analytics
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