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.

Modern data analytics platforms like Databricks have become indispensable for many companies. However Databricks costs can become unpredictable. This article gives four steps to help companies like yours predict Databricks costs and save your company time and money.

Companies are under pressure to deliver faster innovation, enabled by cloud-based data analytics and AI. In order to deliver faster business value, data teams are looking to achieve speed and scale through data and AI pipeline performance and efficiency. A recent MIT Technology Review Insights report finds that 72% of technology leaders agree that data challenges are the most likely factor to jeopardize AI/ML goals.

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.

Adobe launched Adobe Experience Platform Federated Audience Composition, now generally available on Snowflake, allowing organizations to unlock seamless interoperability for marketers by integrating Snowflake's AI Data Cloud with Adobe Real-Time Customer Data Platform (CDP) and Adobe Journey Optimizer.

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.

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.

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.

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.

Picture this: It's Black Friday, and you're circling a packed mall parking lot. Every space is taken, and cars are lined up waiting for spots. You keep circling, but there’s just no place to park and you run out of gas. When you see a java.lang.OutOfMemoryError it’s just like what you experienced in that overcrowded parking lot. The Java Virtual Machine (JVM) has run out of space to "park" new objects in memory. Now here's the thing about Java: it loves objects. It can't get enough of them.