Predictive Analytics & Intelligent Automation in QA with BlueSwan

1. Predictive Analytics & Intelligent Automation in QA with BlueSwan

2. Predictive Analytics & Intelligent Automation in QA with BlueSwan How Predictive Analytics can move your QA organisation one step closer to Continuous Testing  In our world, organizations developing and deploying applications face mounting pressure to deliver better solutions faster while incessantly churning business requirements.  Agile and DevOps application delivery methodologies have had an enormous impact on market responsiveness and Continuous Delivery has augmented IT’s delivery arsenal. Despite these improvements, many companies still face the headwinds of aligning and optimizing their testing resources and struggle with ever-compressing test cycle times. Software delivery teams are not only tasked with delivering assurance faster but also need to be more intelligent about what they test and develop cognitive capabilities that predict and prevent application failures from surfacing before applications reach testing. This article examines the use of analytics in the QA function and explores how it must become a critical component of continuous testing.  Progressive application delivery is increasingly gaining adoption across enterprises  In the past, many organisations relied on QA personnel and tools to help ensure application quality and drive business value. Such traditional testing approaches leveraged human resources to execute massive amounts of application testing tasks manually with the assistance of software technologies. However, while such conventional approaches for application testing raised quality levels and reduced the probability of defect leakage into production, they were inherently inefficient, had difficulty proving value, and were fragmented in their ability to predict application testing issues before they became embedded defects.

3. Predictive Analytics & Intelligent Automation in QA with BlueSwan Progressive application delivery is increasingly gaining adoption across enterprises  In the past, many organisations relied on QA personnel and tools to help ensure application quality and drive business value. Such traditional testing approaches leveraged human resources to execute massive amounts of application testing tasks manually with the assistance of software technologies. However, while such conventional approaches for application testing raised quality levels and reduced the probability of defect leakage into production, they were inherently inefficient, had difficulty proving value, and were fragmented in their ability to predict application testing issues before they became embedded defects. To address this problem, organisations needed not only the means to enable rapid remediation but also the capability to automatically detect software incidents. These ensure that customer-facing or internal business applications are always available and running to support users when they are needed.  Read Full White Paper at: https://www.cigniti.com/resource/white-papers/predictive-analytics-for-qe-with-blueswan