Systems | Development | Analytics | API | Testing

If you're building distributed applications or working in cloud native development, you know that robust connectivity and API governance are the foundations for speed and scale. However, this also holds true in the realm of event streaming. Many top companies now depend on Apache Kafka and Event-Driven Architecture (EDA) for resilience and real-time capabilities.

The Centers for Medicare & Medicaid Services (CMS) finalized the CMS-0057-F Interoperability and Prior Authorization Rule, which marks a pivotal shift in U.S. healthcare, requiring payers, providers, and health IT vendors to enable seamless data exchange through FHIR APIs. The rule is designed to reduce administrative burden, improve care coordination, and empower patients with timely access to their health information.

The education sector is undergoing one of the fastest digital transformations in history. By 2025, the global eLearning market is projected to surpass $400 billion, with mobile learning alone expected to grow by over 20% annually. From K-12 to higher education and corporate training, digital platforms are now the backbone of how students learn, teachers teach, and institutions operate.

For years, QA practices were designed for predictable, rules-based software. AI has upended that reality by introducing risks that traditional methods cannot fully address.

As an application developer integrating analytics into your application, your users expect a scalable, flexible solution that adapts to changing business needs. While organizations strive to capitalize on new AI tools, they’re also still wrestling with big data: massive, fast-moving datasets that traditional tools can’t handle easily.

Traditional automation in software testing is beginning to show its limitations. Once regarded as the benchmark for speeding up QA, now struggles to keep pace with modern software development. Agile methodologies, DevOps practices, continuous delivery, and rapidly evolving user journeys require testing strategies that are more innovative, quicker, and adaptable.The challenge? Old automation frameworks still lean too much on people. They rely on fixed scripts, constant maintenance, and manual oversight.

Do you know that moment when your old on-prem systems creak under pressure? Apps are slow, updates are a nightmare, costs are ballooning, and innovation is bottlenecked by outdated infrastructure? Many organizations are waking up to the fact that keeping things as they are is no longer viable. Application migration to Azure isn’t just a tech upgrade; it’s a strategic move.

Learn how to connect DreamFactory to SAP HANA on-premise and get access to HANA and other SAP ERP’s on HANA with a REST API connector. Instantly auto-generate secure REST APIs, integrate with apps, BI dashboards, and AI pipelines—without custom coding.

Boost query performance by more than 2.5X and reduce storage costs by 50% compared to self-tuned Hive tables, without lifting a finger. Many data teams still need to manually develop and schedule custom tasks to maintain each and every table in their lakehouse, leading to inconsistent query performance and runaway costs.

Key takeaways of embedded BI pricing: TL;DR Interested in pricing for Yellowfin? Request a quote. We’ve all been there: you’ve found the perfect solution for your product, but then you get to the pricing page and see a cost or pricing model that makes your jaw drop. That’s the "sticker shock" we want to help you avoid when buying embedded analytics. While the value of embedding BI is clear, not all pricing models are created equal.