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| Title | Handbook Of Big Data Analytics: Volume 2: Applications In Ict, Security And Business Analytics |
|---|---|
| ID_Doc | 28682 |
| Authors | Ravi V.; Cherukuri A.K. |
| Year | 2021 |
| Published | Handbook of Big Data Analytics: Applications in ICT, security and business analytics |
| DOI | http://dx.doi.org/10.1049/PBPC037G |
| Abstract | Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time. In the first volume of this comprehensive two-volume handbook, the authors present several methodologies to support Big Data analytics including database management, processing frameworks and architectures, data lakes, query optimization strategies, towards real-time data processing, data stream analytics, Fog and Edge computing, and Artificial Intelligence and Big Data. The second volume is dedicated to a wide range of applications in secure data storage, privacy-preserving, Software Defined Networks (SDN), Internet of Things (IoTs), behaviour analytics, traffic predictions, gender based classification on e-commerce data, recommender systems, Big Data regression with Apache Spark, visual sentiment analysis, wavelet Neural Network via GPU, stock market movement predictions, and financial reporting. The two-volume work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics. © The Institution of Engineering and Technology 2021. |
| Author Keywords | Algorithmic contracts; Apache spark; Automated analytics pipelines; Bank customer complaints; Banking analytics; Behaviour analytics; Behavioural sciences computing; Big data; Big data analytics; Big data regression; Business analytics; Business and administration; Business data processing; Ciphertext-policy attribute-based signcryption; Cloud storage; Computer networks and techniques; Contract-driven financial reporting; Data analysis; Data handling techniques; Data privacy; Distributed ledger technology; E-commerce; Evolving spiking neural networks; Financial data processing; Gender-based classification; General and management topics; Gpu; ICT; Information networks; Internet of things; Internet of things; Iot data streams; Neural nets; Other dbms; Parallel hierarchical clustering; Parallel self-organizing maps; Parallelized radial basis function neural network; Privacy-preserving techniques; Recommender systems; Recommender systems; Search engines; Secure big data storage; Secure routing; Security intelligence; Security of data; Smart city; Social and behavioural sciences computing; Software defined networking; Software defined networking; Stock market movement prediction; Stock markets; Traffic prediction; Visual sentiment analysis; Wavelet neural network; Zero attraction data selective adaptive filtering algorithm |
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