Need to deploy APIs and full-stack apps with gRPC and HTTP/2 support? Sign up now to deploy with our free tier and choose your preferred protocol in the control panel or via the CLI. Our thing is to let you deploy your apps globally in less than 5 minutes - and with high-end performance. Not only does this require us to be meticulous about everything composing our infrastructure layer, but also we have to support high-level protocols like WebSockets, HTTP/2, and gRPC.

Usually, when clients come to us with an idea for developing a feature-rich mobile app, they might find it a little difficult to comprehend the workflow and the importance of specific stages. Therefore, one frequently asked question we usually face is, ‘Is it necessary to work on a prototype?’ Well, the answer to this frequently asked question is an ABSOLUTE YES and cannot be overlooked in any part of the development phase.

Quantum Metric uses BigQuery to analyze vast amounts of data to drive customer-centric digital experiences.

Everywhere you look on social media its DevOps, Agile Methodologies, Continuous Integration, Continuous Delivery. You could be forgiven for believing that most organisations and programmes follow these principles. This is not true. Many companies use a Waterfall model which is also known as a linear-sequential life cycle model. In a waterfall model, each phase must be completed before the next phase can begin and there is no overlapping in the phases.

Chad Sanderson is passionate about data quality, and fixing the muddy relationship between data producers and consumers. He is a former Head of Data at Convoy, a LinkedIn writer, and a published author. He lives in Seattle, Washington, and is the Chief Operator of the Data Quality Camp. Without data quality, your data initiatives will fail. Despite that, data teams still struggle to gain buy-in on quality initiatives from executive teams. Here's why: 1.

Migrating to BigQuery from Spark helped Statsig to develop new features for customers and help them run scalable experimentation programs.

Fivetran CEO George Fraser and Snowflake CEO Frank Slootman sat with Data Cloud Now to discuss what they’re hearing from customers in their joint interview.

Organizations are leveraging log analytics in the cloud for a variety of use cases, including application performance monitoring, troubleshooting cloud services, user behavior analysis, security operations and threat hunting, forensic network investigation, and supporting regulatory compliance initiatives. But with enterprise data growing at astronomical rates, organizations are finding it increasingly costly, complex, and time-consuming to capture, securely store, and efficiently analyze their log data.

Data fragmentation and the growing volume of data sources and types are putting increased focus and importance on an organization’s ability to continuously organize, transform and cost effectively deliver real-time data to its entire organization through the cloud.