Systems | Development | Analytics | API | Testing

Cyberattacks are terrifying because of their potential to wreak havoc on a massive scale. The interconnectedness that the internet provides can totally be exploited. Quality assurance teams around the world have to be prepared against such disastrous scenarios, so they sometimes launch authorized cyberattacks on their own systems to check for vulnerabilities. This process is known as penetration testing, or pen testing for short.

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.

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.

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.

In the world of software development, there is an ever-growing need for agility and speed. With competitive markets and constantly evolving user needs, organizations can’t afford to waste time on the development cycle. This is where Continuous Integration (CI) comes in as an essential tool for modern software development practices.

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.

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.

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.

Have you heard this quote from Edwards Deming? – “In God we trust, all others bring data.” In today’s competitive landscape, if you’re not measuring your performance and closely analyzing each relevant data point, you’re not going to see much success with your strategies. This is the golden rule no matter what type of business you run – whether you’re a small, local jewelry store or Coca-Cola. And KPIs (key performance indicators) help us do just that.