Software Testing

In an era of rapid digitization, enterprises are adopting technology at a frenetic pace. The benefits accrued thereby include enhanced productivity, better customer service, scalability of operations, and increased revenue. In all these ways, the cloud has emerged as a key enabler for enterprises in their overall digitization journey. However, with increased technological sophistication, the specter of cybersecurity is also looming large. Time and again, we hear reports of cybercriminals wreaking havoc on connected systems, be it in airlines, electricity grids, banking, or retail. The losses suffered by enterprises and individuals due to such threats continue to mount. According to Cybersecurity Ventures, the annual cost of cybercrime globally is estimated to be $6 trillion. It is almost 1% of the global GDP. As per betanews.com, around 82% of CIOs believe their supply chains are vulnerable to attacks. With the Internet of Things (IoT) and cloud computing making the world more connecte...

With business processes becoming increasingly sophisticated, connected, and comprehensive in their scale, enterprises are relying on next-gen technologies such as robotic process automation or intelligent automation to achieve business transformation. It empowers businesses to better manage their processes, increase productivity and efficiency, and deliver greater customer experiences. Furthermore, enterprises are increasingly leaning towards hiring RPA services to plan, create, and implement a roadmap for digital process automation. In sectors such as manufacturing, BFSI, retail, and logistics, among others, automation has become a powerful tool to reimagine and reinvent business processes. According to statistics, the global RPA market is expected to reach USD 2.32 billion in 2022. It is likely to reach USD 30.85 billion by 2030, at a CAGR of 38.2 percent. (Source: webinarcare.com) RPA automation technology has influenced businesses to look at enhancing the user-friendliness of their...

In this digital age, business enterprises or organizations of all sizes rely heavily on technology to perform efficiently and effectively. However, such reliance on technology also makes them vulnerable to cyber threats and attacks. Malware, ransomware, phishing, hacking, and other cybersecurity threats and attacks can cause severe damage to a business’s reputation, finances, and operations. Further, with time, the sophistication and frequency of cyber-attacks continue to increase, making it challenging for businesses to keep up with these threats using manual processes alone. According to Check Point Research (CPR), global cybersecurity attacks increased by 38% in 2022 in comparison with 2021. To protect organizations against such threats, businesses should have robust measures in place. However, having measures in place is not enough; they need to follow strong cybersecurity testing practices as well. Cybersecurity measures should be tested regularly to ensure their effectiveness in...

Today, business enterprises are operating in a highly competitive landscape with multiple touchpoints, channels, and operating and regulatory environments. For such business enterprises, data has become their most important asset, which is being continuously acquired from all types of sources. These may include IoT networks, social media, websites, customers, employees, the cloud, and many more. Here, data is no longer defined only as highly structured information. They constitute a wide variety of data types and structures emanating from a multitude of sources. With all this high volume of information, the question arises: does the data deliver true value to the enterprise? If enterprises cannot extract timely data insights from business data, then they are not adding any value. The challenge before businesses today is to leverage data in alignment with technology, security, and governance into a cohesive modernization framework to deliver tangible benefits. Although using data from ...

  Computer vision technology helps modern businesses solve a range of complex visual tasks, such as defect detection, self-driving cars, and medical imaging, among others. It has made an impact across sectors, including automotive, retail, healthcare, and others. According to Grand View Research, the market for computer vision is expected to be worth $19.1 billion by 2027, at a CAGR of 7.6%. It is a field of study that encompasses developing algorithms and techniques for interpreting and analyzing visual data from the world around us. This is where data labeling comes into play to train machine learning models for tasks related to computer vision. These models need to be provided with a large amount of data in the form of images or videos that are labeled with annotations. The annotations describe the features present in the data. For instance, solutions to infuse artificial vision in computer systems depend on data annotation, as in the data labeling platform Zastra . Further, d...