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API testing basics for beginners

API (Application Programming Interface) is the building block of software applications. More often than not, APIs are used to access data, facilitate interaction between multiple applications, enable communication between Microservices, etc. While a good deal of software testers perceive working with API as a frightening experience, in reality, APIs are the simplest and most non-complicated way of dealing with applications.

The 6 common data mistakes that could be holding your business back-and how to avoid them

Data is everywhere–driving the evolution of technology, changing the way we do business, transforming what it means to be a customer. Yet, too many businesses are still operating in a data-aware state and not truly adapting to a data-driven mentality. According to Deloitte Insights, just 1 in 10 executives believe that their employees can actually use data to make decisions.

How exploratory testing tools benefit QA teams

Exploratory testing is a successful method for locating undiscovered defects in software. However, many companies request that testers use scripted test cases based on predetermined product requirements rather than exploratory testing. Although scripted test cases help find faults in a product's code, exploratory tests assist the QA team in finding difficult-to-predict problems within the features of the finished product.

Is there a way for software test engineers to manage stress in this culture of hustle?

Hey there, everyone. How are you all doing? I noticed the reply. Hmm. As a result, you claim that your situation is good. Do you actually feel good? Are you getting adequate rest? Having a healthy diet? Do you maintain a clear boundary between your personal and professional lives? When was the last time a production flaw occurred? When did you last snooze like a baby? When did you last take a trip? When did you last speak with your childhood friend? I apologize for asking so many questions.

Distributed Feature Store Ingestion with Iguazio, Snowflake, and Spark

Enterprises who are actively increasing their AI maturity in a bid to achieve business transformations often find that with increased maturity comes increased complexity. For use cases that require very large datasets, the tech stacks required to meet business needs quickly become unwieldy.