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.

Navigating the complex world of data, businesses often grapple with raw, unstructured information; this is where data wrangling steps in, turning chaos into clarity. Seamlessly intertwined with ETL processes, data wrangling meticulously refines and prepares data, ensuring it's not just ready but optimized for insightful analysis and decision-making.

Artificial Intelligence (AI) is quickly becoming the go-to for businesses looking to up their game. Its advances have led to a suite of AI-powered tools that make running a company smoother—from automating redundant tasks to whipping up stunning visuals to redefining customer service. We’ll introduce you to the best AI tools for productivity and provide strategies to integrate AI into your daily operations.

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.

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.

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.

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.

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.

Looking to take the load off your data engineers and IT pros? And help business users create and analyze datasets on their own? You’re in the right place. In this article, we’ll review the best self-service analytics solutions on the market today: We'll look at the main features of each tool, its pros and cons, its best use cases, and user reviews to help you make the right choice. Before we delve into each one, let’s set the tone of what to expect from a good service analytics tool.