Websites and apps are slowly starting to integrate more collaborative features as a means of increasing interactivity and the functionality of various use-cases. Be it a collaborative document or a chat room, one common feature is to show who else is in the space with you. Typically this’ll be done with an Avatar Stack, a collection of icons, each representing a client connected to the space.

Organizations are transforming their industries through the power of data analytics and AI. A recent McKinsey survey finds that 75% expect generative AI (GenAI) to “cause significant or disruptive change in the nature of their industry’s competition in the next three years.” AI enables businesses to launch innovative new products, gain insights into their business, and boost profitability through technologies that help them outperform competitors.

Struggling to keep up with your organization’s hunger for data? That’s an obstacle that many data teams face when their data stack grows and they don’t have complete control over their complex data pipelines. If that’s a challenge you’re looking to solve, you’re in the right place. Below, we’ve curated our list of the best data observability tools every data team should know about.

APIs (application programming interfaces) are increasingly acting as the “missing link” to help organizations integrate all their systems, applications, and databases. So how can you take advantage of API integrations for yourself? The answer is API-led connectivity. API-led connectivity is a systematic approach that uses APIs to seamlessly integrate diverse technologies within an organization, enabling efficient data and application access while fostering agility and innovation.

With updates to our browser user interface (UI), Stories, report navigation and more, Yellowfin 9.10 is an update that further enhances your users' analytics experience. 9.10 brings significant updates. Browse Page UI has received a sleek makeover, simplifying navigation for reports, dashboards, and presentations, catering to both new and experienced users.

Lately, AI and Machine Learning have been the most significant breakthroughs in the software testing space, and they will remain a hot topic for the foreseeable future.

However, the entire change in the development practices has only been triggered considering the extensive need for improving or meeting the end user’s perspective. And the process involves the best of Agile, DevOps testing services, QAOPs, and DevSecOps practices. Talking specifically for DevOps, it not only streamlines development and operations, but helps foster collaboration through enhanced software delivery for added efficiency, quality, and access to automation.

See why Snowflake’s healthcare customers rate the Data Cloud high in performance and cost savings. Each year, KLAS Research interviews thousands of healthcare professionals about the IT solutions and services their organizations use. Since 1996, the analyst firm has been leading the healthcare IT (HIT) industry in providing accurate, honest and impartial insights about vendor solutions and customer satisfaction metrics.

Snowflake’s data cloud has expanded to become a top choice among organizations looking to leverage data and AI—including large language models (LLMs) and other types of generative AI—to deliver innovative new products to end users and customers. However, the democratization of AI often leads to inefficient usage that results in a cost explosion and decreases the business value of Snowflake. The inefficient usage of Snowflake can occur at various levels.

Of the many things one might take for granted, access to banking and financial services may not immediately come to mind. But as a thought experiment, imagine trying to buy a home or a car without the ability to take out a loan. Try depending on cash payments from your employer, or relying on alternative banking solutions like short-term payday loans, check-cashing services, and prepaid debit cards.