Like most organizations today, you’re probably looking to optimize your business model through increased technology adoption. The more successful digital transformation projects look at changing business trends and seek to incorporate those trends within their own specific environment. Similarly, as API technology grows, promising new functionalities and integrations, enterprises should aim to embrace the utility of APIs within their wider technology strategy.

It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.

In today's data-driven business landscape, the ability to predict trends, explain drivers, and act on insights is no longer a luxury—it's a necessity. Yet for many organizations, the path from data to predictive intelligence remains challenging. Data science resources are scarce, and traditional tools often require specialized expertise that most analytics teams lack. At Qlik, we believe that the power of predictive analytics should be accessible to all.

The cloud-based GitLab CI/CD platform allows development teams to streamline their Continuous integration (CI) and Continuous Delivery (CD) pipelines and accelerate their Software Development Lifecycle (SDLC). Adding strict, compliance-based static analysis — as provided by Helix QAC — as new stages to existing GitLab CI/CD pipelines will enhance the SDLC still further, and move your DevOps workflows from Continuous Integration to Continuous Compliance.

The DevOps landscape continues to evolve rapidly. As more organizations embrace DevOps to stay competitive, the landscape is shifting to include more diverse players and specialized offerings. But what's next for the space? Gartner's latest Magic Quadrant for DevOps Platforms report highlights the latest developments and standout players in the space, including Bitrise's growing impact on mobile DevOps.

A prominent global bank was thrust into the spotlight for all the wrong reasons. The institution was hit with a staggering fine – multiple billions – for failing to comply with new data protection regulations that ultimately led to a customer data breach. The breach, which exposed sensitive information, not only resulted in financial penalties but also caused significant reputational damage.

Organizations are harnessing the power of AI to revolutionize products and services across industries. But AI-powered solutions have been getting more sophisticated. We need to redesign and amend our approach to understanding how customers experience these solutions. Unlike traditional products, AI solutions are dynamic, continuously learning and adapting. Traditional metrics may fall short of capturing the nuances of how users interact with AI.

Developer productivity is not just about writing code faster—it’s about creating efficient, self-service environments that minimize friction and reduce the time from development to deployment. In the context of Kubernetes clusters, enhancing productivity means leveraging the right tools and workflows to streamline development, reduce errors, and speed up feature releases. This guide explores the key strategies and tools that can significantly boost productivity in Kubernetes environments.

For life sciences organizations, the key to success is the ability to bring the highest quality products to market quickly and cost-effectively. However, the commercialization process is filled with hurdles that hinder time to market, such as complex regulatory requirements and managing cross-functional collaboration. These challenges require a strategic and well-coordinated approach for successful commercialization.