"We have achieved a 100 percent defect identification rate, which means that there are no false negatives. In the operational model that we built, there is a manual visual inspection in the later phases of the process, so the false reporting rate is permissible to a certain level. We believe …
"Our analysts were very attached to their own set of analytics tools, which they wanted to use on top of BigQuery. But after a while, they began querying data directly through BigQuery itself. It's easy to use and fast on complex queries, and they use Looker Studio to display results."
"Standardizing on Google Maps was a great move for us. We needed a way to improve the whole user experience. A big reason for the popularity of the services throughout Brazil is the familiar Google Maps interface – people don't spend any time learning how to use the app. The …
“We wouldn’t have been able to do this without BigQuery’s ability to analyze data. We’ve talked about developing differentiated learning for years. With machine learning, we can accomplish what we’ve always wanted to do.”
"In video analysis, we need more GPU than CPU. However, most cloud providers tie the amount of CPUs together with GPUs, which means we would have a lot of underutilized CPUs, not to mention the high costs associated with it. One of the biggest benefits of Google Cloud is that …
“We wanted to bring data-driven decision-making to our media strategy to keep our current customers happy as well as attract new ones. We’re already big users of Google Marketing Platform, so using Google Cloud to power a data platform was the obvious choice.”
“The beauty of AI Platform is that it works locally as well as in the cloud. That meant we could test it locally, and then when we went into production, we could host it on App Engine and not have to worry about scale.”
"Google Cloud allowed us to do things that we didn't even think were possible in the very beginning. When we switched to the new system, processing 43 billion events took less than five minutes. That's what a huge impact scaling makes."
“Our existing infrastructure was very simple to use, but also very manual. We needed a more sophisticated solution that could scale at speed while minimizing our overheads. For us, that solution was Google Cloud.”
“BigQuery isn’t just powerful, it democratizes the data. It’s so easy to use even for people who aren’t dedicated software engineers. We can gain valuable insight from live data without forcing some poor data manager to manage our queries for us.”
“It’s about giving people the opportunity to take one simple action every day that makes a difference. If a million people do that, then that can have a huge impact.”
“One thing that's really exciting about data is the engagement. We have a great opportunity to not only help people’s physical health but also their mental health. And the different ways we can interact with them through that data to drive engagement, to motivate them more, to get them to …
"To bring sustainable utilities to market, we need to be both responsive to our customers and responsive to the internal needs of A2A. Google Cloud data infrastructure is the very best available, pulling together the elements we need to build a highly scalable platform that transforms to match our needs."
“One of the critical things we considered for part of this journey was to work closely with the business to make sure we addressed their business and analytical needs.”
"We wanted to remove the obsolescence of the legacy platform that we were using. We needed to modernize and ensure that we had a scalable, globally consistent SAP solution that was optimized for data analytics. That’s why we chose to deploy RISE with SAP on Google Cloud."
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