Husain M.S., Khan M.Z., Siddiqui T. Big Data Concepts, Technologies, and Applications

CRC Press, 2024. — 216 p. — ISBN: 9781032579184.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.NoSQL databases, referred to as “No SQL” or “Not only SQL,” are non-tabular databases and store data differently than relational tables. The standard RDBMS system stores and retrieves information using SQL syntax for deeper analysis. This is done so that better choices can be made. Instead, data in a NoSQL database system can be stored in a wide variety of non-relational formats, such as structured, semi-structured, unstructured, and polymorphic data, across several databases. A NoSQL database system can accommodate the storage of a variety of data. There is no requirement for a NoSQL database, also known as a non-relational data management system, to have a specified schema. NoSQL provides high scalability and availability, and because of this, it is frequently utilized in environments dealing with large amounts of data as well as web applications that operate in real-time, for example, Twitter, Facebook, and Google.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 analytics in healthcare, business, social media analytics, fraud detection and prevention, and governance.Section A UNDERSTANDING BIG DATA.
Overview of Big Data.
Challenges of Big Data.
Big Data Analytics.
Section B BIG DATA TECHNOLOGIES.
Hadoop Ecosystem.
NoSQL Databases.
Data Lakes.
Deep Learning.
Blockchain.
Section C BIG DATA APPLICATIONS.
Big Data for Healthcare.
Big Data Analytics for Fraud Detection.
Big Data Analytics in Social Media.
Novel Applications and Research Directions in Big Data Analytics.