Companies today want to leverage their data to support business intelligence (BI) initiatives, but without the proper data connectivity processes and tools in place, that data could remain locked in silos. Enter the Progress DataDirect Hybrid Data Pipeline (HDP) connectivity solution, which allows companies to securely connect cloud and on-premises data to BI tools. The HDP … continue reading
A recent CIO article revealed a startling reality: 31% of employees admit to sabotaging their company’s generative AI strategy. That’s nearly one in three workers actively slowing down, blocking, or undermining progress. Now layer in the math: most AI initiatives involve dozens of employees. That means statistically, almost every project or proof-of-concept is being impacted by one or … continue reading
Organizations are dealing with unprecedented amounts of data, and while this data has the potential to help drive more informed business decisions and facilitate AI projects, data silos can arise and prevent companies from realizing the true potential of their data. “Integrating diverse data sources requires not only bridging differences in data models and protocols … continue reading
Getting accurate address data for customers is a challenge on its own, but getting accurate legislative district data add an entirely new level of difficulty on top. There are a number of reasons why developers might need access to that data however, such as advocacy groups trying to do outreach that involves connecting voters to … continue reading
A recent email from ASTQB warned testers that to survive in an AI-driven world, they’ll need “broad testing knowledge, not just basic skills.” The advice isn’t wrong—but it misses the bigger picture. The real disruption is already here, and it’s moving faster than most realize. AI systems like AI Script Generation (AISG) and GENI are already generating, executing, and … continue reading
While the industry is racing to develop and implement artificial intelligence into its systems, cultural resistance, a skills gap, and the speed with which AI is changing are just a few of the factors why many AI projects fail. Because of that, most attempts at adopting AI into organizations never make it past the pilot … continue reading
For decades, software testing has been built on a simple idea: humans write tests, machines run them. That model has persisted since the first commercial recorders appeared in the mid-1990s. Testers would record a flow, edit a script, maintain it as the application evolved, and repeat the cycle endlessly. Tools improved incrementally, but the basic … continue reading
Melissa, a provider of data quality solutions, is making it possible for customers to run its SQL Server Integration Services (SSIS) components in Azure Data Factory through the Azure-SSIS Integration Runtime. This brings the power of Melissa’s data quality features to the cloud, providing customers greater flexibility in where their data is stored. SSIS is … continue reading
At Broadcom’s recent Spark VSM Summit, the theme was “VSM evolution meets AI revolution.” After the event, SD Times sat down with Broadcom’s Jean Louis Vignaud, the head of ValueOps at the company, to discuss the AI revolution and its connection to value stream management. This interview has been edited for length and clarity. DR: … continue reading
A recent study by Broadcom about the state of strategic portfolio management revealed the influence of digital transformations and AI on the role of the project management office (PMO). Further, it revealed common challenges in software development, such as budget constraints, skill shortages, and team coordination issues. Broadcom’s Brian Nathanson, head of product management for … continue reading
At its annual development conference POST/CON, Postman announced several new updates across its platforms to make it easier to design, test, deploy, and monitor AI agents and APIs. One of the main announcements is the introduction of Agent Mode, an AI agent that can interact with all of Postman’s core capabilities. Specifically, it can create, … continue reading
As every company moves to implement AI in some form or another, data is king. Without quality data to train on, the AI likely won’t deliver the results people are looking for and any investment made into training the model won’t pay off in the way it was intended. “If you’re training your AI model … continue reading
Many infrastructure technology teams believe they have mastered infrastructure automation, but the data tells a different story. We commissioned a survey to explore the state of infrastructure automation, and this research uncovered a stark gap between perception and reality. While 45% of organizations believe they have achieved a high level of infrastructure automation, only 14% … continue reading
With AI making its way into code and infrastructure, it’s also becoming important in the area of data search and retrieval. I recently had the chance to discuss this with Steve Kearns, the general manager of Search at Elastic, and how AI and Retrieval Augmented Generation (RAG) can be used to build smarter, more reliable … continue reading
