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Preserving Data Privacy in Life Sciences: How Snowflake Data Clean Rooms Make It Happen

The pharmaceutical industry generates a great deal of identifiable data (such as clinical trial data, patient engagement data) that has guardrails around “use and access.” Data captured for the intended purpose of use described in a protocol is called “primary use.” However, once anonymized, this data can be used for other inferences in what we can collectively define as secondary analyses.

The 16 Best Automation Testing Tools to Use in 2024

It’s hard to know who to trust for automated testing tools. With so many options, deciding which one will fit your specific needs can be tough. That’s why we’re breaking down the top tools in the industry, their advantages and disadvantages, the tests they’re used for, their price points, and more. We’ll also share user reviews and give you our recommendations to help you find the perfect fit for your business needs.

A Software Engineer's Tips and Tricks #4: Collaborating on Visual Studio Code with Live Share

Hey there! We're back for our third edition of Tips and Tricks, our new mini series where we share some helpful insights and cool tech that we've stumbled upon while working on technical stuff. Catch up on the previous posts: All of our posts are super short reads, just a couple of minutes tops. If you don’t like one of the posts, no problem! Just skip it and check out the next one. If you enjoy any of the topics, I encourage you to check out the "further reading" links.

Analyzing AWS Audit Logs in Real Time Using Confluent Cloud and Amazon EventBridge

Last year, we introduced the Connect with Confluent partner program, enabling our technology partners to develop native integrations with Confluent Cloud. This gives our customers access to Confluent data streams from within their favorite applications and allows them to extract maximum value from their data.

Deploy applications with confidence with Tricentis NeoLoad and DataDog

In today’s digital landscape, ensuring the optimal performance of your applications is paramount for delivering seamless user experiences. However, identifying potential bottlenecks is not easy. This analysis is one of the single most important activities in performance testing, but it’s often the most difficult one, and a misstep can cause significant setbacks.

Exploring the Future of User Experience in Banking and Fintech

It’s Monday morning, and Sam woke up to a gentle sound on his phone. It’s not an alarm but his new financial pal—a voice-activated AI assistant. This friendly voice, tailored to his financial goals, provides a personalized morning briefing of his accounts, highlights upcoming bills, and even suggests budget-friendly options for his breakfast. After a busy workday, Sam stared at his evening coffee.

Targeting Robot at a Specific Window: A Deep Dive into Katalon Studio

Hello, Katalon users and software testing enthusiasts! Today, we’re going to delve into a topic that has been buzzing in our community forum: How to target a robot at a specific window in Katalon Studio. This blog post is aimed at experienced software testing professionals who are familiar with Katalon, or those looking to switch to the Katalon Platform.

Xray continues to excel in Customer Service with the new Stevie Awards in 2024

With the Silver and Bronze Stevie Awards, Xray reaffirms its commitment to outstanding customer support and service excellence. Xray, a leader in software testing solutions, is proud to announce its recent awards in the 2024 Stevie Awards. It secured a Silver Stevie for Front-Line Customer Service Team of the Year and a Bronze Stevie in the Customer Service Department of the Year category for Computer Software companies with up to 100 employees.

What Separates Hybrid Cloud and 'True' Hybrid Cloud?

Hybrid cloud plays a central role in many of today’s emerging innovations—most notably artificial intelligence (AI) and other emerging technologies that create new business value and improve operational efficiencies. But getting there requires data, and a lot of it. More than that, though, harnessing the potential of these technologies requires quality data—without it, the output from an AI implementation can end up inefficient or wholly inaccurate.