Systems | Development | Analytics | API | Testing

With the GA of Apache Spark stored procedures in BigQuery, users can extend their queries with Spark-based data processing via BigQuery APIs.

Enterprise Strategy Group compared BigQuery to alternative cloud-based enterprise data warehouse solutions.

If you’ve been following our news, you know we just announced free fractional GPU capabilities for open source users, enabling multi-tenancy for NVIDIA GPUs and allowing users to optimize their GPU utilization to support multiple AI workloads as part of our open source and free tier offering.

Welcome back to Yellowfin Japan’s ‘How to?’ blog series! In our previous blog, we went through how to create big number and vertical column charts in Yellowfin, and the many different charting options available in Yellowfin Canvas. Before we re-visit our regular series, we want to share a shorter dashboard walkthrough.

Creating an effective application migration strategy is crucial for organizations seeking to migrate their applications to a new environment, such as a cloud platform or a different on-premises infrastructure. A well-planned migration strategy ensures a smooth transition, minimizes downtime, and mitigates potential risks and challenges. Here’s what you need to do in order to create an application migration strategy.

Distributed architectures have become an integral part of modern digital landscape. With the proliferation of cloud computing, big data, and highly available systems, traditional monolithic architectures have given way to more distributed, scalable, and resilient designs. In this blog, we look at what makes an application distributed and how distributed applications work to bring about high availability, scalability, and resilience.

This blog post is about testing microservices and distributed systems with JMeter. It will focus on the principles of performance testing applications that are architected this way. We will not look at which JMeter samplers to use in order to generate a load against microservices or how to configure these samplers. This post will consider best practise and consideration in designing your performance testing when faced with these applications.

Think back just a few years ago when most enterprises were either planning or just getting started on their cloud journeys. The pandemic hit and, virtually overnight, the need to radically change ways of working pushed those cloud journeys into overdrive. Cost-effective adaptability was essential. And the companies that could scale up or scale down quickly were the ones that navigated the pandemic successfully. Migrating to the cloud made that possible.

Enterprises looking to increase productivity and optimize business processes are increasingly turning to artificial intelligence (AI). AI can meet these expectations—but only with the right enabling technology. Intelligent automation at scale across the organization can offer a strategic approach to incorporating AI into complex business processes.

The potential impact of AI in banking appears boundless. A 2023 McKinsey report found that effectively incorporating generative AI tools into business operations could lead to annual operational savings ranging from $200 billion to $340 billion for the global financial services industry. These cutting-edge technologies can also enhance customer satisfaction, attract more potential customers, and improve employee experience.