In recent years, software development has experienced significant growth and increased emphasis on quality. For instance, conventional software testing has primarily been mechanical, where defects are detected and corrected during testing. Although this method has been used for some time and has been somewhat helpful, it has been considered unsuitable in the current context of derivation, integration, and frequent updates.
This is where predictive analytics comes in—a new approach that turns the model from one of post facto testing and design to one of pre-testing. Real-time analytics is a process that identifies potential defects and failures by analyzing historical data, leveraging machine learning, and applying statistical models to predict future occurrences. This enables development teams to take preventive measures to prevent system failures, reducing downtimes and enhancing software quality. This is not just a change in the tools employed in developing these software systems; it is a change mandated to enable software development in a new way.
