Systems | Development | Analytics | API | Testing

Driving Innovation with NVIDIA AI Data Platform: A View from Hitachi Vantara

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.

The Easiest Way to Power Real-Time AI: Confluent Announces Delta Lake Support & Unity Catalog Integration for Tableflow

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.

What Companies Get Wrong About Data Ownership and What to Do Instead

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.

Build Observable Data Flywheels for Production with Iguazio's MLRun and NVIDIA NeMo Microservices

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.

Feed Your AI Models the Data They Deserve - with Countly

Anyone who has tried to build a recommendation engine or a churn predictor knows the moment the excitement fades. The prototype looks good in the notebook, but the training data contains typos, half-missing properties, and events that somehow morphed between different devices. The model stumbles, engineers lose faith, and everyone wonders where all that AI magic went.

Allium's Blueprint for Scaling Blockchain Data with Data Streaming | Life Is But A Stream Podcast

Blockchain may be decentralized, but reliable access to its data is anything but simple. In this episode, Ethan Chan, Co-Founder & CEO of Allium, shares how his team transforms blockchain firehoses into clean, queryable, real-time data feeds. From the pitfalls of hosting your own data streaming infrastructure to the business advantages of Confluent Cloud, Ethan reveals the strategic decisions that helped Allium scale from 3 to nearly 100 blockchains, without burning out their engineering team.