BigQuery Graph is now GA: the knowledge foundation for the agentic era
Discover how BigQuery Graph enables native graph analytics and AI agent grounding, delivering connected context across enterprise data without moving data.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
How we stop malicious code? Python Sandboxing Explained
A technical overview of how Centerprise Agent Builder runs user-submitted and LLM-generated Python outside the main server process - covering Python.NET, worker isolation, callback tokens, and Docker-level containment.
New MCP tools for Declarative Pipelines
Qlik's MCP server just got three new lookup tools built for data engineering. They connect directly to your Qlik Cloud tenant, so coding agents can pull the real project values a pipeline needs instead of working from an empty template, find spaces and data connections by name, and browse the tables and views available on a connection, just by asking in natural language. That means easier declarative pipeline creation, with real tenant context built right into your prompt for faster, more accurate iteration.
Agentic AI Just Rewrote the Data Engineer's Job Description. Here's What IT Leaders Need to Know.
Gartner predicts that 70% of today's data engineering tasks will be fully automated by 2030. I put that number to Tim Garrod, Qlik's Head of Product Management for data integration and quality, on a recent Qlik Insider session, and his answer is the one every CIO, CDO, and VP of IT should sit with: automation doesn't make the data engineer obsolete, it makes the good ones ten times more valuable. AI amplifies skilled judgment. It doesn't replace it.
Your AI Feature Shipped. Now, Will Users Trust It?
The question product and engineering teams ask before shipping an AI feature is usually simple: does it work? Is the model accurate enough? Are the outputs reasonable?
Turn every spec change to a green test: A step-by-step guide to AI-assisted API test sync
Imagine this scenario: your engineering team just pushed a spec update. A field was removed, an endpoint renamed, a new required parameter appeared on the payments API. Nobody told QA. Three days later, your regression suite lights up red across a dozen tests that have nothing to do with the actual bug. They’re failing simply because the tests are stale. Someone spends the next afternoon manually diffing the old spec against the new one, hunting for what changed, then rewriting test steps by hand.
What's Driving the Great AI Re-Architecture?
As enterprise AI scales, traditional data architectures are reaching their limit. Workloads are becoming more distributed, data movement is accelerating, and tech leaders face growing pressure to justify AI spend while delivering real business impact. Chief Technology Officer Sergio Gago breaks down key findings from Cloudera’s latest global survey of enterprise architects, data architects, and cloud leaders.
How Sales & RevOps Leaders Use Spotter for Natural Language Data Analysis
How does our sales and revenue operation teams use Spotter, our agentic analyst, to instantly access and analyze their data using natural language? In this video, you'll see how Spotter makes data interrogation easy and reliable. Learn how to: Explore Data Sets: Quickly understand what data you have access to, where it is pulling from, and get immediate examples of what you can ask. Get Instant Answers: Type a natural language question (like "What's the booked ACV this quarter by region?") and instantly receive easy-to-read charts and deep analyses.
How ThoughtSpot's SVP of Revenue Strategy Saves Sellers 2 Hours of Research Per Account
Our own sales team was losing up to 2 hours per account just switching between tools. Here's how they got that time back. In this video, our SVP of Revenue Strategy walks through how her team built a single sales hub with AgentSpot, pulling data from ThoughtSpot, Salesforce, Gong, and external intent signals into one workflow. What you'll see: What's hot in your territory: the accounts showing real buying intent, based on search trends and ICP fit.
10 Best Client Dashboard Software for Agencies & Digital Marketers in 2026
Let’s be real—clients don’t care about how much effort you put in. They only care about results. If you’re not delivering clear, real-time performance insights with zero fluff, you risk losing their trust—and their business. That’s why a good client dashboard software is a necessity. It can take the guesswork out of reporting, and give your clients a crystal-clear view of their campaigns without endless emails or confusing spreadsheets.