TY - GEN N2 - This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students. DO - 10.1007/978-3-031-15542-0 DO - doi AB - This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students. T1 - Role of data-intensive distributed computing systems in designing data solutions / AU - Pandey, Sarvesh, AU - Shanker, Udai, AU - Saravanan, Vijayalakshmi, AU - Ramalingam, Rajinikumar, CN - QA76.9.B45 N1 - Includes index. ID - 1454364 KW - Big data KW - Electronic data processing SN - 9783031155420 SN - 3031155424 TI - Role of data-intensive distributed computing systems in designing data solutions / LK - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-15542-0 UR - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-15542-0 ER -