For enterprises relying on SAP systems, ensuring smooth operation through updates, integrations, and daily operations is crucial. Manual testing of these complex systems increases time to market and the likelihood of human error. The solution? SAP testing automation, which enables faster, more reliable testing, ensuring your business-critical processes run smoothly without bottlenecks.

The first step is often the hardest, and in software testing, this is especially true. When presented with a system, how do you go about and decide what to test? Standing in the middle of the unknown, we need guidance, and learning about test case design techniques is a good place to start. In this article, we’ll show you: Let’s dive in!

Artificial Intelligence (AI) has become an inseparable part of our lives, revolutionizing industries, transforming workspaces, and influencing how we interact with technology. From virtual assistants like Siri and Alexa to advanced machine learning algorithms driving breakthroughs in medicine, AI is everywhere. But as AI continues to evolve, a growing question lingers: Is AI making us smarter or more dependent?

Are self-driving cars safe? The software in modern cars contains more than 100 million lines of code that enable many different features — cruise control, speed assistance, and parking cameras. And, the code within these embedded systems only gets more complex. This trend will continue as cars of the future become more connected. Cars are increasingly dependent on technology. And they will progressively become more autonomous — and ultimately self-driving.

Sidekiq is one of the most popular open-source background job libraries for Ruby. As one of ActiveJob's most popular backends, it's often used to run asynchronous jobs in Rails applications. It leans on Redis to manage queues and jobs, which makes it fast. Developers can run background jobs using Sidekiq with or without ActiveJob, and we'll explore both in this article. Just as useful - Sidekiq scheduled jobs allow you to run a job after a given amount of time or at a given time.

Have you noticed how quickly the retail industry is changing? It's all thanks to digital transformation, which is happening at an incredible pace. We bet you're curious about why this shift is happening and what's driving it. Don't worry, you're not alone in your questions. Many people are wondering about the same thing. With each passing day, we see new technologies and IT solutions being adopted by retailers to stay ahead of the competition and offer better user experiences.

Check Point Research found that global weekly attacks rose by 7% in Q1 2023 versus the same quarter last year, with each organization facing an average of 1248 attacks per week. In 2023 researchers noticed that it’s taking organizations an average of 49 days to identify a cyberattack. That’s terrifying, isn’t it? But, what does this mean? Is this a signal that your business needs a foolproof web development strategy to prevent your website from cyberattacks?

A SQL injection attack is an attempt to modify the syntax of a SQL query executed in conjunction with a user-initiated action within a software application. Some examples of user-initiated actions include searching for a product within an e-commerce catalog, adding a comment to a blog post, and creating a new user account. In each of these scenarios, the user uses a form to submit input (e.g.

Gen AI has the potential to bring immense value for marketing use cases, from content creation to hyper-personalization to product insights, and many more. But if you’re struggling to scale and operationalize gen AI, you’re not alone. That’s where most enterprises struggle. To date, many companies are still in the excitement and exploitation phase of gen AI. Few have a number of initial pilots deployed and even fewer have simultaneous pilots and are building differentiating use cases.

Every enterprise is modernizing their business systems and applications to respond to real-time data. Within the next few years, we predict that most of an enterprise's data products will be built using a streaming fabric – a rich tapestry of real-time data, abstracted from the infrastructure it runs on. This streaming fabric spans not just one Apache Kafka cluster, but dozens, hundreds, maybe even thousands of them.