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Author Bhatia, Jasmeet, author.

Title IBM Cloud Pak for Data on IBM zSystems / Jasmeet Bhatia, Ravi Gummadi, Chandra Shekhar Reddy Potula, Srirama Sharma. [O'Reilly electronic resources]

Edition [First edition].
Publication Info. [Place of publication not identified] : IBM Redbooks, [2023]
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Description 1 online resource (40 pages) : illustrations
Summary Most industries are susceptible to fraud, which poses a risk to both businesses and consumers. According to The National Health Care Anti-Fraud Association, health care fraud alone causes the nation around $68 billion annually. This statistic does not include the numerous other industries where fraudulent activities occur daily. In addition, the growing amount of data that enterprises own makes it difficult for them to detect fraud. Businesses can benefit by using an analytical platform to fully integrate their data with artificial intelligence (AI) technology. With IBM Cloud Pak® for Data on IBM zSystems, enterprises can modernize their data infrastructure, develop, and deploy machine learning (ML) and AI models, and instantiate highly efficient analytics deployment on IBM LinuxONE. Enterprises can create cutting-edge, intelligent, and interactive applications with embedded AI, colocate data with commercial applications, and use AI to make inferences. This IBM Redguide publication presents a high-level overview of IBM zSystems. It describes IBM Cloud Pak for Data (CP4D) on IBM zSystems and IBM LinuxONE, the different features that are supported on the platform, and how the associated features can help enterprise customers in building AI and ML models by using core transactional data, which results in decreased latency and increased throughput. This publication highlights real-time CP4D on IBM zSystems use cases. Real-time Clearing and Settlement Transactions, Trustworthy AI and its Role in Day-To-Day Monitoring, and the Prevention of Retail Crimes are use cases that are described in this publication. Using CP4D on IBM zSystems and LinuxONE, this publication shows how businesses can implement a highly efficient analytics deployment that minimizes latency, cost inefficiencies, and potential security exposures that are connected with data transportation.
Subject Artificial intelligence.
Cloud computing.
Intelligence artificielle.
Infonuagique.
artificial intelligence.
Artificial intelligence
Cloud computing
Added Author Gummadi, Ravi, author.
Potula, Chandra Shekhar Reddy, author.
Sharma, Srirama, author.
ISBN 9780738461069 (electronic bk.)
0738461067 (electronic bk.)
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