Ibm Cloudant Database As A Service Advanced Topics

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IBM Cloudant: Database as a Service Advanced Topics

Author: Christopher D. Bienko
language: en
Publisher: IBM Redbooks
Release Date: 2015-04-17
This IBM® RedpaperTM publication describes advanced topics for IBM Cloudant, a NoSQL JSON document store that is optimized for handling heavy workloads of concurrent reads and writes in the cloud, a workload that is typical of large, fast-growing web and mobile apps. You can use Cloudant as a fully-managed DBaaS running on public cloud platforms like IBM SoftLayer or via an on-premise version called Cloudant Local that you can run yourself on any private, public, or hybrid cloud platform. This paper is the third in a series of IBM Redbooks® publications on Cloudant. Be sure to read the others: IBM Cloudant: The Do-More NoSQL Data Layer, TIPS1187 and IBM Cloudant: Database as a service Fundamentals, REDP-5126.
IBM Cloudant: Database as a Service Advanced Topics

Author: Christopher D. Bienko
language: en
Publisher: IBM Redbooks
Release Date: 2015-04-17
This IBM® RedpaperTM publication describes advanced topics for IBM Cloudant, a NoSQL JSON document store that is optimized for handling heavy workloads of concurrent reads and writes in the cloud, a workload that is typical of large, fast-growing web and mobile apps. You can use Cloudant as a fully-managed DBaaS running on public cloud platforms like IBM SoftLayer or via an on-premise version called Cloudant Local that you can run yourself on any private, public, or hybrid cloud platform. This paper is the third in a series of IBM Redbooks® publications on Cloudant. Be sure to read the others: IBM Cloudant: The Do-More NoSQL Data Layer, TIPS1187 and IBM Cloudant: Database as a service Fundamentals, REDP-5126.
Handbook of Research on Mathematical Modeling for Smart Healthcare Systems

Advances in healthcare technologies have offered real-time guidance and technical assistance for diagnosis, monitoring, operation, and interventions. The development of artificial intelligence, machine learning, internet of things technology, and smart computing techniques are crucial in today’s healthcare environment as they provide frictionless and transparent financial transactions and improve the overall healthcare experience. This, in turn, has far-reaching effects on economic, psychological, educational, and organizational improvements in the way we work, teach, learn, and provide care. These advances must be studied further in order to ensure they are adapted and utilized appropriately. The Handbook of Research on Mathematical Modeling for Smart Healthcare Systems presents the latest research findings, ideas, innovations, developments, and applications in the field of modeling for healthcare systems. Furthermore, it presents the application of innovative techniques to complex problems in the case of healthcare. Covering a range of topics such as artificial intelligence, deep learning, and personalized healthcare services, this reference work is crucial for engineers, healthcare professionals, researchers, academicians, scholars, practitioners, instructors, and students.