Google Cloud Serverless for Apache Spark, now available in BigQuery is an open-source, zero-ops, high performance, and unified analytics platform.

We are proud to announce a new integration between MLRun, the open-source AI orchestration framework, and NVIDIA NeMo microservices, by extending NVIDIA Data Flywheel Blueprint. This integration streamlines training, evaluation, fine-tuning and monitoring of AI models at scale, ensuring high-performance, low latency and lowering costs while significantly reducing the manual effort required through intelligent automation.

Most companies believe they own their customer data. Most are wrong. Data is your most powerful asset for fueling decisions, improving customer experiences, and providing a competitive edge. But if your customer, marketing, or product teams rely on third-party analytics tools, there’s a great chance you don’t actually own your data. It’s processed, stored, and sometimes even monetized by vendors who decide your access and control levels.

In the age of AI, the hunger for fresh, reliable data to power machine learning (ML) models and real-time analytics is insatiable. Yet, organizations frequently hit roadblocks when trying to bridge their operational data in motion, typically flowing through Apache Kafka, with their data at rest in data lakehouses. On one side, you have the data streaming platform, the central nervous system managing the real-time flow of business events.

The rapid acceleration of AI adoption is transforming how enterprises design their data infrastructure, driving the need for robust, scalable, and energy-efficient solutions. At Hitachi Vantara, we’re building the future of AI storage by collaborating with NVIDIA to close the gap between data and AI compute. Our mission: help organizations unlock faster, smarter insights with an AI-ready data pipeline.

Microsoft Power BI is a ubiquitous business intelligence (BI) solution entry point that can create a good foundation for analytics capabilities at any company. Its Power BI Embedded tier allows for embedding data visualizations, dashboards and reports into your applications, while using the broader Microsoft Azure Cloud infrastructure. The key challenges Power BI Embedded presents, however, is complexity.

Why data‑savvy business users are moving beyond simple prompts to automated GPT‑powered sheets and pipelines that handle millions of rows and deliver governed insights at speed.