Systems | Development | Analytics | API | Testing

AI for UX design: 5 best practices for product designers

AI is no longer a fringe experiment: it’s a mainstream mandate. But with that shift comes a new kind of pressure: to act quickly, to appear modern, to bolt on something “intelligent” before someone else does. For many teams, this leads to reactive choices. Features get prioritized because they sound impressive, not because they solve a real user problem. Familiar interfaces get copied instead of questioned.

Demo: Streaming Agents automate competitive pricing in real time

Streaming Agents enable you to build, deploy, and orchestrate event-driven agents natively on Apache Flink and Apache Kafka. By unifying stream processing and agentic AI workflows, they leverage fresh context to continuously monitor and act on what’s happening in the business. In this demo, Brenner Heintz, Staff Technical Marketing Manager at Confluent, shows how to build agents that automate real-time competitive price matching on sales orders.

Seamless Storage Integration: Managing PostgreSQL Environments

PostgreSQL is rapidly being adopted by enterprises large and small. Some estimates show as many as 60% are using it in some form or fashion. For anyone who isn’t on board yet, there are many reasons to consider it. To paraphrase their own site, PostgreSQL, is a powerful, open source object-relational database that uses and extends the SQL language, combined with features that safely store and scale the most complicated data workloads.

Charts Are Just the Start: How Databox Helps Agencies Take Action, Faster

Dashboards are great — but what about doing something with that data? In this clip, an agency shares how Databox helps them spot issues early, make adjustments fast, and stay proactive with features like Scorecards, Notifications, and real-time reporting. Your data should help you move, not just measure.

7 Effective BI Dashboard Components in 2025

Ever feel like your company's data is an untapped resource? We understand the frustration when your data isn't translating into clear, actionable insights for your team. A truly effective business intelligence (BI) dashboard should be a guide, not a barrier. It helps users understand what's happening and what they can do next, transforming a chaotic data landscape into a single, intuitive source of truth. That requires some work.

Real-Time AI Agents Powered by Apache Kafka, Apache Flink, and Google Cloud

Discover how developers and data teams can build agentic AI applications with the combined power of Google Cloud AI services and Confluent Cloud’s real-time data streaming platform. This video showcases the joint value of integrating Apache Kafka, Confluent Schema Registry, Kafka Connect, and Apache Flink to enable seamless, real-time communication between AI agents. What you’ll learn: With Confluent and Google Cloud, you can go beyond AI experiments to build scalable, enterprise-ready multi-agent systems powered by real-time data.

ERP Data Struggles: How To Get Real-Time Reporting in Excel

You can never have too much data, right? But sometimes it feels like that’s the problem when you’re trying to get your enterprise resource planning (ERP) system to play nice with Excel and quickly give you the reports you need. It’s a common challenge for finance teams, and you can fix it. Creating a bridge to make all that ERP data easily accessible in Excel is the key to getting the business intelligence (BI) reports you need quickly.

Lakehouse Logic: Why Object Storage is the New Analytics Engine

Data analytics boils down to a simple objective. To provide people – and increasingly AI agents – with the right information, in the right place, at the right time. That's it. It's easy to state. But historically difficult to achieve. The good news is the landscape is changing.

A Starter Guide to Cloud ETL Tools

In today's world of Internet Technology and the need for instant access to a wide range of information, companies are constantly receiving unprecedented amounts of data from various sources and in different formats. Sorting through this mass of data to find patterns and actionable insights is nearly impossible. This is where the process of Extract, Transform, and Load (ETL) and, more specifically, cloud-based ETL platforms designed for low-code data integration, becomes invaluable.