The omnipresence of software cannot be ignored. It is synonymous with today’s connected world. Our lives are heavily influenced by software. As a result of our industry’s rapid growth, we are creating code at a faster pace than ever before. One thing that often gets overlooked amidst all this exponential growth is the loss we are making because of poor quality & code.

It is 2023, and technology continues to advance at a rapid pace; the field of software testing is constantly evolving. From automation to artificial intelligence, the future of software testing looks very different from what it has been in the past. Software testing is critical for any development of high-quality, reliable software. However, testing has become increasingly challenging as software becomes more complex and user expectations rise.

Successful usability testing takes time and expertise to plan and execute. Moderated usability testing involves a process of user research, participant recruitment, testing user flows, and analyzing data. The end results will uncover prioritized problem areas that, when addressed, will provide new ways to satisfy and retain your users. Different UX methods are dynamically used depending on the team’s goals, product, and audience.

In recent years, manufacturers faced major disruptions. Supply chain issues, unexpected product demand spikes, and delivery driver shortages led to longer lead times. While you can’t completely control external factors like these, you have far more control over your own internal manufacturing cycle times. This post will cover what cycle times are, the benefits of reducing them, and four strategies to help with cycle time reduction. .

With today’s accelerated development schedules, your team will likely rely on high-quality testers to help create great user experiences and improve software testing outcomes. Many companies have turned to on-demand freelance testers to ramp up in-house teams for better, more thorough QA coverage. Here’s the catch; this strategy only works if the testers you employ have the right skills for the job.

For the past 30 years, the primary data source for business intelligence (BI) and data visualization tools has generally been either a data warehouse or a data mart. But as enterprises today struggle to cope with the growing complexity, scale, and speed of data, it’s becoming clear that the data tools of 30 years ago weren’t designed to handle the enterprise data management challenges of today - especially with the growing variety and amounts of data that enterprises are generating.

In the agile development methodology, the velocity of testing holds the key to delivering the best quality software within the stipulated budget and time constraints. As such, this drives the need to automate the testing process. Most software development teams visualize test automation as a discreet step in the delivery lifecycle instead of viewing it as a designed sequence of steps.

Self-service analytics is fast becoming a necessity, not a luxury, in the modern enterprise. More businesses want to provide staff with self-service BI tools they can all use, without needing IT help or technical knowledge. This helps drive a data-driven culture across the organization, open up access to data to more people, and unlock actionable insights.

The term “accessibility” refers to a software system’s usability by individuals without physical disabilities or impairments as well as those who do. Businesses may make digital material accessible to persons with impairments by doing web accessibility testing. Business owners must ensure that their digital material complies with the ADA and Web Content Accessibility Principles because more nations are enacting laws to open web sources to everyone (WCAG).

In a digital-first world, delivering business apps with high efficiency and top-notch quality is critical to your business success and customer satisfaction. Oracle is a major ERP application used by the world’s biggest companies to ensure business runs smoothly, but Oracle deployments are heavy, risky, and slow. How can organizations make them more efficient?