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Latest Blogs

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.

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.

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.

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.

Graph API: Boost Your Data Skills

In today's data-driven world, the ability to seamlessly connect, manage, and manipulate vast amounts of data is paramount for businesses and developers alike. Graph API stands at the forefront of this technological frontier, offering robust tools that facilitate complex data interactions within applications. This powerful API provides a framework for accessing and integrating data points in an intuitive and effective manner, supporting dynamic data structures across various platforms.

What is Metadata Management? Benefits, Framework, Tools, Use Cases, Best Practices

Before shedding light on metadata management, it is crucial to understand what metadata is. Metadata refers to the information about your data. This data includes elements representing its context, content, and characteristics. It helps you discover, access, use, store, and retrieve your data, having a wide spread of variations. Metadata of an image. Image by Astera. Let’s look at some of the metadata types below.

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.

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.

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.