“Quality is more important than quantity. One home run is much better than two doubles.” – Steve Jobs In the world of software testing, this quote couldn’t be more relevant. If you’re a manual tester, you know the pressure to deliver high-quality results, often within tight deadlines and limited resources. Yet, with today’s fast-paced software development cycles, meeting these demands through manual testing alone is increasingly challenging.

Scalability testing ensures your software application can handle increased loads as user demand grows. This makes it crucial for businesses looking to support growth and maintain high availability.

ClickHouse is a high-performance, columnar database designed for analytics and big data applications. One of ClickHouse's standout features is its ability to perform filtering directly on compressed data, enabling faster results compared to traditional relational databases. While working with ClickHouse, you will often encounter the WHERE and PREWHERE clauses, both of which are used to filter data. But what is the difference between WHERE and PREWHERE, and when should you use one over the other?

Imagine having a powerful tool that revolutionizes how you communicate and do business with your customers. That’s precisely what Customer Relationship Management, or CRM, offers. It’s a category of software solutions combining data-driven technology to enhance customer interactions and improve business performance.

Design, speed, and simplicity are the winning flavors for any mobile banking app. By possessing these characteristics, the fintech app can entice any smartphone enthusiast, the number of whom is steadily increasing. The industry’s major players recognize that the pervasiveness of mobile phones in our lives must be used as a tool to win loyal users for FinTech businesses.

Today’s fast-paced development environments require new approaches to testing. Enter continuous performance testing. Unlike traditional performance testing, automated continuous performance testing is part of every build, monitoring the application continuously under increased load. With continuous performance tests, organizations with lots of users can expect to improve the customer experience, prevent major outages, and find and resolve issues faster.

The insurance industry is experiencing a profound shift, moving away from traditional models toward more personalized, data-driven solutions. The “Pay-As-You-Live (PAYL)” model leads this change, a groundbreaking life and health insurance approach that adjusts premiums based on each individual’s lifestyle choices and behaviors. Rather than relying on general statistics and broad risk categories, Pay-As-You-Live customizes coverage to reflect the unique health habits of each policyholder.