As a very hands-on VP of Product, I have many, many conversations with enterprise data science teams who are in the process of developing their MLOps practice. Almost every customer I meet is in some stage of developing an ML-based application. Some are just at the beginning of their journey while others are already heavily invested. It’s fascinating to see how data science, a once commonly used buzz word, is becoming a real and practical strategy for almost any company.
In the first blog of the Universal Data Distribution blog series, we discussed the emerging need within enterprise organizations to take control of their data flows. From origin through all points of consumption both on-prem and in the cloud, all data flows need to be controlled in a simple, secure, universal, scalable, and cost-effective way.
When it comes to hybrid cloud and digital transformation, it’s all about application services and leveraging appropriate on-premise, service provider, and hyperscaler cloud resources and services seamlessly and efficiently.
Google’s data cloud enables customers to drive limitless innovation and unlock the value of their data via its robust offerings under a single, unified interface. By migrating their data ecosystems to Google Cloud, organizations are able to break down their data silos and harness the full potential of their data. However, historically, migrating data warehouses has not been an easy task.
For decades, hundreds of enterprise Oracle ERP customers have taken advantage of the industry-leading capabilities for operational reporting and strategic analytics offered by Angles for Oracle (formerly Noetix.) If your organization is one of those customers, we want to make you aware of some exciting new features recently introduced to the latest platform version that improve agility, collaboration, and integration.
