Systems | Development | Analytics | API | Testing

Are you wondering where all your team’s time is being spent? Is it all spent on managing software that promises agility for finance teams? In today’s fast-paced and ever-changing business landscape, it is imperative for organizations to be agile. Being able to embrace change and respond quickly has become a key factor in the success of any business.

Autodesk, Envision Pharma, and Cemex use Fivetran and Snowflake for real-time analytics and faster decision-making.

In this second blog in a multi-part series, learn how SAP attempts to limit customer choice and discourages customers from accessing SAP data in third-party data platforms.

Engineering teams now move faster than ever. In 2025, they build smarter, ship quicker, and rely heavily on AI tools and continuous delivery pipelines.

Welcome to the latest entry in Yellowfin Japan’s long-running ‘How to?’ blog series. This series of blogs aims to provide a step-by-step guide of how to get the most out of your Yellowfin BI experience, such as how to create your own Yellowfin dashboards. Catch up on the series below.

API versioning is essential for managing changes without breaking your system. In microservices, where APIs are the backbone of communication, versioning ensures stability, backward compatibility, and smooth updates. Here’s a quick breakdown of what you need to know.

Software release cycles are accelerating. In fact, 85% of organizations now release at least once per month, with a 51% increase in automated testing spend last year alone. Yet API quality still breaks down. Why? APIs sit at the center of this acceleration, but as velocity increases, many organizations face a persistent challenge.

If your BI and analytics tool isn’t powered by Agentic RAG AI, you’re missing out on advanced AI capabilities that enhance efficiency and visibility into data. Whereas agentic AI can work autonomously and without human intervention, RAGI AI combines the best information retrieval methods available with the power of AI. The result is deep knowledge of organizational data that improves over time.

Let’s start with DevOps, the buzzword that changed how we think about building and shipping software. These days, every college student and other professional wants to become a DevOps engineer. If you are an aspiring DevOps engineer or already working as a DevOps engineer, this blog will help you understand the difference between Platform engineering and Devops Platform engineering is really changing every company’s perspective on developing platforms.

Business intelligence platforms analyze vast amounts of data, requiring visualization engines that balance performance, flexibility, and ease of use. Traditional charting libraries treat each chart type as a distinct entity, requiring separate logic and code for each. This approach leads to code duplication, limited reusability, and reduced maintainability. Additionally, it’s cumbersome to effectively layer or combine visual elements due to these libraries’ rigid composability.