SAP HANA Scale-out and Virtualization

whitePaper | October 6, 2022

It is not unusual to see software development trends change year after year. The pandemic has only accelerated the whole process, and it seems that the trends are changing even faster. What was once considered as acceptable practice in software development might no longer be the case in the foreseeable future. This is why startup founders and big corporation managers should be aware and well-informed of where all the software industry trends are heading to and how to strategize in the best possible app to develop and place an app.

whitePaper | May 31, 2022

End-to-End (E2E) testing has traditionally been seen as a ‘final frontier’ of sorts in software development.

whitePaper | August 14, 2020

As consumers and customers, we are accustomed to easy, intuitive and superfast transactions driven by data. Therefore, businesses have the various challenges of managing and mining the data they produce and use, but also ensuring that their digital experience is 100% reliable for their customers — so the chain of trust is never broken.

whitePaper | September 28, 2022

Architecting IT infrastructure has never been more challenging than it is today. Many enduser workloads, such as semiconductor design, autonomous driving development, and life sciences and healthcare are growing more complex every day. With that complexity comes growing demand on IT.

whitePaper | May 25, 2022

In the past few years, artificial intelligence (AI) has proved to be much more than just a buzzword, successfully redefining the way that businesses work. From finance to healthcare, various industries have shown tangible outcomes from using AI as a part of their solutions, reiterating the immense possibilities this technology can provide for the world.

whitePaper | May 15, 2023

The future of AI is hybrid. As generative AI adoption grows at record-setting speeds1 and drives higher demand for compute,2 AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential – just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices. A hybrid AI architecture distributes and coordinates AI workloads among cloud and edge devices, rather than processing in the cloud alone. The cloud and edge devices, such as smartphones, vehicles, PCs, and IoT devices, work together to deliver more powerful, efficient, and highly optimized AI.