Building a strong data foundation on Google Cloud Platform
The long-term opportunity for companies lies in applying Google’s heritage of machine learning and analytics at web-scale to real-world data relevant to your business. Google Cloud Platform enables modest-sized teams to aggregate and run machine learning workloads on massive data to do predictive analytics. All this and much more powered by modernized data warehousing platform that can help you with –
The first step to migration begins with understanding of where the customer lies in their cloud journey. Established enterprises have built up increasingly complex software environments like:
As a premier Google Cloud partner, MediaAgility can help you to connect your data silos with modern data warehousing and migrating all of your data to Google Cloud Platform in just two phases –
Kick off your new Google Cloud Platform project with a focus on your foundational architecture, technical design, reference pipelines, long-term operations, and planning for your project.
Spotify chose Google in part because its services for analyzing large amounts of data, tools like BigQuery, are more advanced than data services from other cloud providers.
Google BigQuery delivers a cost-effective and fast analytics environment. BigQuery is a huge differentiator that lets us offer cutting-edge services without driving up our staffing and IT costs.
With genomics data increasing day by day, we’re not too far from a point when labs cannot keep up with the growing computational demand,” Dr. Abhyankar says. “With Google Cloud Platform, we don’t need to worry about running out of space or compute— we can focus on the science