DataOps.live, the software company dedicated to helping organizations build and manage their essential Data Applications and Data Products more effectively, has released the latest version of its revolutionary DataOps platform, combining a unified developer experience with the ability to perform DataOps at scale.
“No-Fear Enterprise Data Engineering at Scale means enabling Data Product developers to build faster, handling more data domains at the same time, building larger and more sophisticated Data Products at the same time, while data engineers remain 100% in control,” says Thomas Steinborn, VP of Products. “We are delivering enhancements across five functional areas to deliver on this premise.”
DataOps on Kubernetes – We’re excited to announce support for Kubernetes (our most requested feature) which enables customers to dynamically scale their enterprise DataOps infrastructure within their highly managed, highly available cloud architecture while using compute resources mor efficiently and reducing cost. Load balance all your workloads across nodes, and let Kubernetes ensure high availability for all your data pipelines.
Also Read: Mastech Digital Announces Leadership Change In Its Data and Analytics Services Business Segment
DataOps Unified Developer Experience – DataOps.live is launching its new unified developer experience, a fully hosted IDE with all the pre-packaged components and plugins needed for a highly efficient Snowflake development experience. Just click one button and you have all the power, control and usability features of a locally installed IDE like Visual Studio, without ever installing anything. It’s available wherever and whenever you need it. This is the final step in enabling Data Product developers to be as efficient and productive as software developers. Day-to-day developer productivity can increase by up to 50% depending on the amount of development time they are spending every day.
DataOps.live introduces full “Data Product” objects – Dataops.live now supports Data Product objects as code, bringing a more natural, streamlined experience to Data Product creation and management. Data Product owners can organize projects by Data Product and dataset; data engineers can find the one table they need among thousands and have fewer merge conflicts; new developers have a faster learning curve; and Data Product stakeholders can have their Data Product refreshed in their data catalogs in seconds.