Systems | Development | Analytics | API | Testing

AI Is Either Reshaping Your Business or Decorating It

At Qlik Connect, one question kept coming up in conversations with leaders: “Which AI vendor should we pick?” But I think that’s the wrong starting point. The better question is: What kind of company do you want to become over the next three years? Right now, most organizations are heading down one of two paths with AI. Some are bolting it onto existing workflows to improve efficiency.

Turn Your Agents Into Kafka Experts with Skills. Live from Current London

Most AI agents are generalists that struggle with the nuances of streaming data and Kafka infrastructure, often leading you down a rabbit hole with many tokens spent. In this session, live from Current London, we’ll show you how to close the context gap with Skills for Kafka: structured files that are playbooks and level-ups for agents to handle complex multi-step tasks like reviewing schema changes, critiquing DLQ policies and auditing topics for best practice. We will walk through how these skills work, demonstrate the different ways to use them (including with MCP servers) in Cursor and Claude.

From Analytics Platform to an AI Operating System: Data Lakehouse in the Agentic AI Era

The lakehouse architecture was developed with the mission to combine the unstructured scale of the data lake with the structured performance of the data warehouse. This shift unified enterprise data and delivered the first true "single source of truth". But in 2026, the mission has expanded.

Why 90% of Data Strategies Fail to Make Money

Want your data strategy to actually drive revenue? @SPGlobalMarketIntelligence’s Saugata Saha and ThoughtSpot’s Cindi Howson break down why data strategies fail when they disconnect from business goals. To win, you need to solve real customer pain points and move past the bottleneck of report prep. Watch the new episode of on your preferred listening platform! Music: “The Clermont” by Flash Fluharty Licensed via PremiumBeat, ID: P9IHFMDYNZCKLEFZ.

Enterprise AI Security with ClearML: A Complete Series Summary

Over a seven-part series of posts and videos, ClearML’s Enterprise AI Security series covered every layer of securing an AI platform in production, from who gets in to what gets recorded. This post brings it all together in one place: what each layer does, why it matters, and how the layers connect.

Data Warehouse Design: A Complete 2026 Guide (with examples and templates)

Most data warehouse projects fail. Not because the technology is wrong. Because the design is. Three weeks for a number that should take three minutes. AI agents generating plausible reports nobody can trace. Two ERPs naming the same metric differently. The spreadsheet swamp. The fire drill before every audit. These problems live in the warehouse layer, in how data is modeled, governed, and made available to the people and AI agents that read from it.