Systems | Development | Analytics | API | Testing

Evolve25: Customer Fireside Chat with Banco do Brasil

Learn how the oldest bank in Brazil manages over 800 AI solutions and 5,500 GenAI use cases while maintaining a "Responsible AI" framework. Discover the bank's three-block ROI strategy focusing on operational efficiency, customer satisfaction, and new business models. This session is a must-watch for enterprise leaders navigating the intersection of legacy infrastructure, culture shifts, and Agentic AI.

How to Implement Your First ML Function in Streaming

The most effective way to adopt streaming machine learning (ML) is not by rebuilding your entire platform but by adding a single, high-value inference step to your existing data flow. This incremental approach allows you to transition from batch-based processing to real-time decision-making without the risk of a "big bang" migration, ensuring that your microservices architecture remains agile and responsive. What Is Streaming ML? ML in streaming is the practice of.

Why Your AI Pilot Won't Make It to Production (And What to Do About It)

Most AI pilots fail to reach production not because the models don’t work, but because enterprises struggle with data governance. While pilot-phase AI projects demonstrate impressive results in controlled environments, they hit governance walls when moving to enterprise-scale deployments. This post examines why AI initiatives stall before production and provides a governance-focused approach for breaking the cycle.

Confluent Cloud for Government Achieves FedRAMP Moderate: Mission-Ready Data Streaming for Federal Agencies

Federal agencies must perform a high-stakes balancing act: Modernize legacy systems, break down data silos, and deliver real-time citizen services—all while operating under strict security and compliance requirements with constrained budgets and staff. Today, we're announcing that Confluent Cloud for Government (CCG) is now available on the FedRAMP Marketplace, with FedRAMP Moderate authorization achieved through the competitive FedRAMP 20x Pilot program.

From Dumb Pipes to a Smart Data Plane: Introducing Schema IDs in Apache Kafka Headers

Apache Kafka powers massive, mission-critical data streams at enterprises worldwide. But in many organizations, those streams still behave like dumb pipes: raw JSON or bytes flowing between services, limited governance, weak contracts between teams, and data that’s hard to reuse for analytics or artificial intelligence (AI).

Your Analytical Edge Starts with You - A ThoughtSpot International Women's Day Spotlight

"Your lived experience is your analytical edge." For International Women's Day, we sat down with women leading the future of Data & AI: Women In Data's Sadie St Lawrence, NextEnergy Group's Lydia Collett, and ThoughtSpot's Eugenia Losada-Gamst Martínez. They shared what it actually takes to thrive in this industry: Hit play to hear it in their words. Be part of the conversation shaping the future of Data & AI.

Snow Report: What's Happening At Snowflake In March

Hear what’s new at Snowflake in March, from major product launches to upcoming community events, and more. Next generation Snowflake Notebooks are now generally available, delivering a familiar Jupyter-based experience directly in Snowflake workspaces. Online model inference in the online feature store is also generally available, enabling millisecond predictions for real-time use cases like fraud detection and personalized recommendations, with no extra infrastructure to manage.

insightsoftware Recognized in the 2025 Gartner Magic Quadrant for Financial Planning Software

In 2025, insightsoftware was recognized in Gartner’s Magic Quadrant for Financial Planning Software. The recognition focuses on insightsoftware’s JustPerform product, which offers web-based budgeting, planning, and forecasting with an Excel-like interface and self-service reporting, dashboards, and analytics.

Claude Can Now Build Inside Astera Centerprise. Here's How.

Astera Centerprise is already one of the most AI-forward data platforms available. Its built-in agentic AI creates data models, builds ETL/ELT pipelines, generates source-to-target mappings, orchestrates workflows, prepares data, and deploys schemas to production, all through natural language. You describe what you need; the AI uses real Centerprise tools to build it.