Systems | Development | Analytics | API | Testing

End Data Disparity | Building Partnerships To Drive Change

Sep 8, 2025 By Snowflake Inc. In Snowflake
In this premiere episode from the new "End Data Disparity" video series, host Ryan Green chats with Benoit Dageville, Snowflake Co-founder and President of Product, about the challenge of addressing the problem of global data inequalities. The discussion kicks off with information about the cross-sector advisory board Snowflake is establishing to drive the development of collaborative solutions. They also discuss such topics as the role AI will play in improving ESG data quality, which promises to positively impact ESG monitoring and reporting.
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katalon

How to Debug Agentic AI: From Failed Output to Root Cause

Sep 8, 2025 By Katalon In Katalon
In traditional QA, debugging means tracing a failed test step to a broken function, a missed config, or bad data. There's usually a clear defect, a fixable cause, and a predictable outcome. But in agentic AI systems where outputs are shaped by language, memory, tool use, and learned behavior failure is rarely that clean. Instead, it looks like: If Blog 4 taught us how to design tests that stress these systems, this blog is about what to do when those tests fail.
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ghost-inspector

9 Test Automation Best Practices for Browser Testing

Sep 8, 2025 By Ghost Inspector In Ghost Inspector
Whether you’re new to test automation or you’ve been utilizing it to save time for years, here’s our best advice for maximizing your automation testing productivity and avoiding mistakes. Automated testing entails much more than simply creating tests and enabling them. A “set it and forget it” approach won’t get you very far with automated tests — particularly automated browser tests, which interact with the ever-changing frontend of your application or website.
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keploy

The Complete Guide To Low Code Automation: Everything You Need To Know

Sep 7, 2025 By Amaan Bhati In Keploy
Low code automation promises to be more palatable and less time-consuming. There is a wide range of technology options for low code automation; as more "no code" tools become available, and more tools that claim to be "low-code" are rolling out on the market, it is rational for developers to become worried in terms of productivity deficiencies, overtime costs, and the costs borne by consumers if downtime occurs.
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keploy

Test Automation 2030: Rethinking Test-Pyramid Strategies For The AI-Era

Sep 6, 2025 By Neha Gupta In Keploy
Manual testing can’t keep up with today’s fast-moving, AI-powered software development. Test automation isn’t just about saving time-it’s about surviving in a landscape where releases happen daily and bugs can cost millions. Now since AI-generated code is increasing, quality control and ownership becomes more important. From the classic Testing Pyramid to modern takes like the Honeycomb and Trophy, automation strategies are evolving fast.
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keploy

Regression Analysis: The Key To Smarter, Data-Driven Decisions

Sep 6, 2025 By Ayush Gupta In Keploy
In the age of data, numbers have to be meaningful in a bid to inform intelligent choices. Regression analysis is a great statistical tool utilized to reveal the interconnectedness among variables. From forecasting sales to having knowledge of medical outcomes, it converts raw data into practical knowledge. It assist businesses and researchers in accurately estimating, identifying inefficiencies, and benefiting from improved outcomes.
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bugraptors

The Digital Imperative: Why Cloud Audits Are Crucial in 2025

Sep 5, 2025 By Himanshu Chauhan In BugRaptors
As more businesses embrace cloud computing, a very important question comes up: how can we make sure that our digital assets are safe, efficient, and compliant in a dynamic, multi-tenant environment? Even though cloud providers offer strong security, the shared responsibility model puts a lot of pressure on enterprises to keep track of their own data and programs. This is when cloud auditing becomes very important.
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katalon

Compliance & Audit in Agentic Systems - Testing for Safety, Ethics, and Traceability

Sep 5, 2025 By Katalon In Katalon
Agentic AI systems don’t just need to work — they need to be explainable, traceable, and auditable. In regulated environments like banking or healthcare, it’s not enough to pass test cases. You must prove what the AI did, why it did it, and whether it stayed within policy. One company’s AI assistant began recommending high-risk financial products to sensitive users — and no one knew when it started or why. The fix?
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dreamfactory

Synthetic Data Pipelines and the Future of AI Training

Sep 5, 2025 By Kevin McGahey In DreamFactory
Synthetic data pipelines are reshaping how AI models are trained. They generate artificial datasets that mimic real-world patterns, solving challenges like data scarcity, privacy concerns, and bias in training data. These automated systems streamline the entire process, from data creation to integration, offering faster and more scalable solutions compared to traditional methods.
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