Systems | Development | Analytics | API | Testing

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Combat the Risks of an Aging Banking System

Recent headlines have highlighted some of the severe risks of older core banking systems, namely aging user interfaces and a lack of governance. The accounting foundation of an older core remains solid, but the ability to provide good governance, enforce business rules and present a user-friendly interface to the business person is often lacking.

Tips for Javascript Perfomance Testing

No user likes to spend time waiting for a web page to load. No web developer likes a website or app to fail either. It’s important to focus on creating quick loading pages with error-free code. JavaScript is used to build the majority of the dynamic, real-time applications. JavaScript’s strength is in the context of apps that update content dynamically with minimal latency. JavaScript performance testing should be a priority for ensuring a good end user experience and optimal performance.

Our Shared Responsibility Model

There’s a common misconception that as soon as a business signs up for a solution from a cloud service provider (CSP), that the CSP will automatically ensure all their dealings in that cloud environment are safe and secure. As dedicated as Cloud Service Providers are to cybersecurity, that’s simply not possible. Your cloud provider has no control over the customer data you share, the aptitude of your employees, or how you optimize your own on-premises security and firewalls.

CDP Endpoint Gateway provides Secure Access to CDP Public Cloud Services running in private networks

Cloudera Data Platform (CDP) Public Cloud allows users to deploy analytic workloads into their cloud accounts. These workloads cover the entire data lifecycle and are managed from a central multi-cloud Cloudera Control Plane. CDP provides the flexibility to deploy these resources into public or private subnets. Nearly unanimously, we’ve seen customers deploy their workloads to private subnets.

Powering Algorithmic Trading via Correlation Analysis

Finding relationships between disparate events and patterns can reveal a common thread, an underlying cause of occurrences that, on a surface level, may appear unrelated and unexplainable. The process of discovering the relationships among data metrics is known as correlation analysis. For data scientists and those tasked with monitoring data, correlation analysis is incredibly valuable when used for root cause analysis and reducing time to remediation.