“To begin with, we knew that Google Cloud Platform was half the price of other cloud platform providers, but the savings we make with Google Cloud Platform have continued with improvements to the platform. Preemptible VMs are one example. Another is the Nearline backup capability on Google Cloud Storage. We …
"We want to do what we think is going to create the most value. We're trying to do what's right, regardless of the rules that are already set. We're redefining the status quo with our online sales model."
“Many of our clients are amazed by the speed of our analytics running on Google Cloud Platform. We help them complete analyses of the interests of customers and prospects in just a few seconds.”
“With our previous database, some of our complex queries could take a whole weekend to process. But BigQuery is a really powerful technology. It’s fast and scales seemingly endlessly. We’ve already noticed a significant decrease, often to seconds. And our most complex computations now take a few minutes.”
"We work with banks, regulators and clients to identify gaps in the market, and find ways to close them with products that help deliver the financial services vision for the country as a whole."
“Within a month, we progressed as much as we would have in a year and a half.”
“Google Cloud tools suite helped us not only to build the product, but also to improve the environment which we already have.”
"I had to work out how we could best leverage our technology to improve our healthcare. So, I thought we have all this data, we must mine it for insights."
"BigQuery has helped us work orders of magnitude faster than we did with an on-premises database. A query that used to take our engineers 15 to 20 minutes now takes about 15 to 20 seconds for a doctor using our frontend."
"We want to create a sustainable, cost-effective cloud strategy that will provide flexibility to support business decisions over the next five years, so we're looking at solutions that can grow with us. That’s what we’ve found in Google Cloud and its BigQuery data warehouse."
“The cloud environment we were using wasn’t well integrated with our network, resulting in a number of challenges, particularly when it came to security, scalability, and managing our infrastructure. Google Cloud was much more suitable and offered us a greater degree of flexibility.”
“We’re making the same tools that previously demanded expensive hardware available through Compute Engine. Everyone has their own data pipelines and does things slightly differently, but we’re able to ensure that people can collaborate, whether they’re using a VM or on-prem hardware.”
"We invested in a Data & Analytics team to foster a new era of data-driven decisions at our bank. As a result, we managed to support new ideas based on robust insights, aiming for higher customer satisfaction, and leveraging digital transformation, as well as developing financial solutions to serve our …
"Our main reasons for choosing Google Cloud were the advantages of its analytical tools BigQuery and Vertex AI, its AutoML services to accelerate the development of AI-based models, and better resource utilization to deploy a business domain-oriented data platform and self-service analytics."
"We started this process with networking, authentication, and billing strategies. Later on, we created data layers in Cloud Storage and BigQuery to accommodate the on-premises solution's information through an integrated pipeline. Only then did the analytics and machine-learning initiatives begin."
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