Digital transformation is a driving force behind new models and approaches today. Enterprises need to adapt quickly and creatively to reap the benefits of the digital economy. One key aspect of this transformation involves cloud-based SAP testing, essential in building a reliable SAP production and release environment. This insightful blog explores the strengths and capabilities of Cigniti, SAP, and Tricentis, which are vital to ensuring successful large-scale SAP transformations.

GPU as a Service (GPUaaS) serves as a cost-effective solution for organizations who need more GPUs for their ML and gen AI operations. By optimizing the use of existing resources, GPUaaS allows organizations to build and deploy their applications, without waiting for new hardware. In this blog post, we explain how GPUaaS as a service works, how it can close the GPU shortage gap, when to use GPUaaS and how it fits with gen AI.

On top of their industry-leading cloud infrastructure, Amazon Web Services (AWS) offers more than 15 cloud-based analytics services to satisfy a diverse range of business and IT use cases. For AWS customers, understanding the features and benefits of all 15 AWS analytics services can be a daunting task - not to mention determining which analytics service(s) to deploy for a specific use case.

Exploratory testing marks the connection where creativity meets discovery. This method isn’t just about ticking off a list; it's about venturing into the unknown, armed with curiosity and a keen eye for detail. It's a journey that's best embarked upon as a team, where each member's unique perspective and expertise illuminate different facets of the software, uncovering insights that might otherwise remain hidden.

The business of governance is not easy. Public sector organizations face a range of obstacles from corruption to lack of transparency to red tape—obstacles that have the potential to erode public trust in institutions and hinder economic development. That’s probably why, in virtually every country around the world, popular culture lampoons the intricacies of government bureaucracy.

Tech debt is the cost of choosing quick solutions over better ones, requiring future rework. It is a fact of life for developers–when work piles up and deadlines approach, you prioritize what’s most important. In the short term, taking the easy road keeps your release schedule on track and your applications running smoothly, at least on the surface.

Artificial intelligence (AI) can transform the way your enterprise does business—but if you can’t quickly implement AI in your business processes, you’ll just as quickly fall behind competitors. This is where low-code AI tools can help. Over the past decade, low-code platforms have enabled software engineers, professional developers, and employees with minimal coding experience to build new digital, automated solutions using drag-and-drop interfaces.

In February, Snowflake released a slew of new features that continue to expand the scope of what you’re able to do with Snowflake, including the public preview of Hybrid Tables. Read on to learn more about everything we announced last month.

In our latest research, conducted this year with AIIA and FuriosaAI, we wanted to know more about global AI Infrastructure plans, including respondents’: 1) Compute infrastructure growth plans 2) Current scheduling and compute solutions experience, and 3) Model and AI framework use and plans for 2024. Read on to dive into key findings! Download the survey report now →

Organizations are constantly seeking more efficient ways to extract, transform, and load (ETL) data into their data warehouses. Snowflake, is one of the leaders in cloud data warehousing, has traditionally recommended ETL/ELT processes for data ingestion and extraction. However, for organizations building internal data products, there is a new kid on the block: API generation. Here’s the key things to know from this article.