Transforming Data Management Using Machine Learning

whitePaper | July 28, 2022

Data protection has become an integral and essential part of any successful business. The need to provide a powerful, scalable, and simple disaster and operational recovery solution is at an all-time high.

whitePaper | September 28, 2021

Read on to learn how the Cloudera Data Platform accelerates your on-premises data analytics operations in a manner reminiscent of the cloud, unlocking flexibility, scale, and power from your traditional, on-premises data center.

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.

whitePaper | August 25, 2022

The new PowerMax 2500 and 8500 storage systems with PowerMaxOS 10 feature some of the most advanced performance, data protection, data reduction, and data mobility servicing enterprise workloads and applications. The new PowerMax systems come with large DRAM for user data and persistent memory for metadata, end-to-end NVMe, 100 Gbit RDMA fabric, real-time machine learning, 64-bit native file services, seamless cloud mobility, and ability to deliver millions of IOPS at submillisecond latency.

whitePaper | January 27, 2020

AWS maintains a standards-based risk management program to ensure that the HIPAA-eligible services specifically support the administrative, technical, and physical safeguards required under HIPAA. Using these services to store, process, and transmit PHI allows our customers and AWS to address the HIPAA requirements applicable to the AWS utility-based operating model.

whitePaper | March 12, 2020

Operational Acceptance Testing (OAT) is the penultimate phase of Acceptance Testing in a Software Testing Life cycle and is the last defence line between a software development project and deployment of software on production. FFor decedes, Operational Acceptance has been undermined and misunderstood. Where User Acceptance has been written about and hailed as a final phase in testing before production. User Acceptance is but one side of the coin, Operational Acceptance is the other.