"From a business point of view, we intend to keep our high growth rates. Expanding brings complexity, and complexity slows you down. We have to keep agile to adjust our value proposition to customers and continue growing."
"Besides its massive compute scalability, the cost flexibility of Google Cloud aligns perfectly with our company values. Plus, with BigQuery ML, it's been really easy to incorporate cost predictions so our customers have even more control over their cloud rendering jobs."
“More than 24 virtual machines, 240 virtual cores, and 1.5 terabytes were scaled, provisioned, and fully managed. Thanks to the ease of working with Google Cloud, we estimate that we were able to accelerate the delivery of the project by 20%.”
“We especially liked that Google Cloud would process upgrades for us automatically, meaning we simply restart our machines and can scale from six cores to eight cores, or from 8 GBs of RAM to 32 GBs of RAM.”
“On the education side, Google Cloud big data tools help us directly integrate into classroom and student workflows, while empowering academic research and other university work.”
“It took a lot of time to prepare data for various teams. We’d have unannounced schema changes and have to validate data selection. From finding, preparing, validating, and delivering data, it sometimes took up to four and a half weeks to complete requests. Simple tasks were, in fact, quite difficult. …
“We needed a flexible solution that could adapt to any request, so we began working with Google Cloud and Localyse to migrate our genomics pipeline to the cloud.”
“It’s not unusual for organizations to be concerned about cloud security and privacy, but then after implementation, they realize it’s stronger than their previous approaches. We are happy to help UZ Leuven come to this realization as they confidently migrate their genomics pipeline to Google Cloud.”
“We had to undertake node upgrade maintenance once a month ,and it took our team several hours to complete each time. Furthermore, sometimes we needed to change node instance types to optimize resources for application updates, and this could take a few days. With Google Kubernetes Engine in Autopilot mode, …
"Financial markets are becoming fundamentally decentralized and unbundled. The services that large legacy banks and brokerage firms used to offer are being supplanted by Tradier's microservices and APIs, which power innovation."
"We chose Google Cloud because of the availability of managed AI services, especially those related to high-quality natural language processing with a response time compatible with our services, which are in near real time."
“With our AI-based symptom checker and clinical support technology, which we have been developing since 2013, we will make healthcare accessible to everyone by creating a ‘search engine’ for healthcare. We are going to go full throttle to realize our company mission as soon as possible.”
“People trust us with very sensitive information. One of our main reasons for opting for Google Cloud was the need to work with a provider who takes data protection seriously.”
"The beauty of BigQuery is that we could start small and grow, without large upfront costs. That made it easy to do proofs of concepts, prove to people that it would work, get support for the solution, and grow data utilization."
“Our engineering team had no capacity to help, and we needed Looker to do it quickly. The POC was fast and well executed. We felt so much support from every aspect of Looker.”
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