Systems | Development | Analytics | API | Testing

9 Best Agentic AI Data Quality Tools in 2026

Bad data doesn't announce itself. It flows silently through your data pipeline, lands in your dashboards, and feeds your AI models until someone downstream notices the numbers don't add up. By then, the damage is done: a flawed forecast, a miscalibrated model, a compliance gap you didn't see coming. For data engineers and analytics managers, this is a significant operational risk.

Agentic Data Management: What It Is and Which Tools Deliver It

Data engineering teams often spend a substantial portion of their time maintaining pipelines instead of building new data products, particularly as environments become more complex. Many organizations still struggle with stale, inconsistent, or low-quality data, leading to delayed or less reliable decision-making. Traditional data management tools alert you to problems but leave the fixing to human hands.

Your Mobile Tests Just Got a Lot Less Repetitive | What's New in Katalon Studio | Give It a Test

Katalon Studio's latest update is out. Sơn Huỳnh (Support Engineer, Katalon) walks through what's new in Katalon Studio 11.3 and 11.4 — from a faster, more direct Mobile Recorder to saving your AI-generated API tests straight into the repository.

How Enterprise Teams Are Automating AI Compliance at Scale | Perforce 2026

AI has changed how fast software ships. It hasn't changed how compliance gets done, until now. In this session, Perforce CTOs Anjali Arora and Rod Cope are joined by Nico Kruger, Senior Director of Global Sales Engineering, to break down why traditional compliance can't keep pace with AI-native development, and what replaces it. Topics covered: This is the fourth and final session in the "When AI Starts Shipping Code" webinar series, exploring how AI is reshaping software delivery from development through governance, testing, and now compliance.

Consumer offset mapping in Kafka-to-Kafka replication

If you replicate data between two distinct Kafka clusters, you already know the payloads can match while the offsets might not. This post is about how K2K 2.0 now also keeps consumer committed offsets in sync between the source and the target so consumer groups can fail over in a Disaster Recovery situation, avoiding large re-reading of data or row skips. This offers the community more choice for DR than just MirrorMaker2 and Confluent solutions have until now.

Introducing K2K 2.0: Enterprise Kafka DR - without vendor lock-in

Summary Kafka has become the backbone of the real-time enterprise. The streams it carries are not only time, but business critical: a fraud event isn't processed, a sales order not fulfilled, a trade not settled. Yet we heard a recurring theme from Kafka teams: their business is running critical streaming applications without proper Kafka resiliency.

What Is a Generative Engine Optimization Checker and How Does It Work?

With Artificial Intelligence (AI) quickly changing how people discover information online, search is no longer limited to traditional search engines. This creates a new challenge for businesses and marketers in terms of knowing whether generative engines can find, understand, and recommend their content.

Qlik Answers and the Automate Agent - Hello World - Part 3

In Part 3, we keep things simple with a “Hello World” example that shows how to create a basic Qlik Automate workflow and trigger it directly from Qlik Answers. You’ll see how an insight can quickly become an action—all within Qlik, without a complicated setup. Check out Parts 1 and 2 for the full series.