Much of the healthcare industry has made significant advances in technology over the past decade, progress that has been met with new regulations, disruptions to treatment protocols, and, inevitably, ever-rising patient expectations. To better navigate or overcome these new challenges, healthcare organizations should be looking to solutions that prioritize interoperability and ease of access to accurate, relevant data. Delivering Interconnected Experiences for Patients As the healthcare industry’s focus toward interoperability and value-based care models increases, delivery of care will grow more interconnected. Most healthcare organizations are familiar with the data silos and obsolete technology systems that have long stood in …

Many businesses continue to rely on legacy systems because they are convenient to use, inexpensive to maintain, and—more than anything—they work. Modernizing these antiquated systems sounds good, but in reality, it’s far from easy. These systems are often deep-rooted throughout day-to-day business operations and entrenched within the technology landscape. It would be an arduous task to rip and replace, to say the least. However, incumbent processes often stand in the way of an organization’s ability to expand and adapt in the face of growing market competition. Challenges introduced by legacy systems include: Obsolete technologies: Repetitive maintenance of obsolete and out-dated …

In an ever changing and evolving technology environment, agility is key to keep pace with the disruptive application development changes. Software teams involved in application development specifically, using DevOps, are under pressure.  Development teams must move faster than ever, test earlier, release early, release often and not compromise any quality or cost. Traditional IT operational approaches are not sufficient to meet these new demands. Customers want application updates quickly and error free.  To meet this demand, development teams are required to increase application release efficiency and frequency. That drives the need for enhanced collaboration, automation and information sharing among stakeholders. …

Machine learning (ML) is one such technology that has tremendously benefited financial services and banking industry. Bad decision making costs organization in terms of time, profitability and reputation. But the real cost of bad decisions is neither losing revenue nor reputation; it is an opportunity to delight customers. The chances are that organizations are more likely to make more bad decisions than good ones, thanks to the onslaught of data. The best way to reduce the cost of bad decision making is to find and fix it, before decision-making team acts on it, machine learning as a subset of data …

Have you implemented a manual testing process only to discover you’re struggling to understand the complexities involved in long testing cycles. Do the time-consuming, resource-intensive and repetitive tasks making you annoyed. Are you noticing a far from satisfactory ROI? Managing manual test execution tasks can be complex and difficult Many companies face these challenges because 80% of their time is spent on repeated iterations and execution of the code which are all tasks a legacy testing process simply can’t do. That’s why it is important to invest in automating manual processes. Businesses these days are compelled to leverage technology to …