Today we announced new core data fabric features associated with our Data Product Platform, to support high-scale operational uses cases in the enterprise.
Table of Contents
Automated Data Catalog
Dynamic Data Virtualization
Edge integration and deployment
Data Product Platform already runs the 3 biggest data fabric deployments in the world, and we built these new capabilities to accelerate implementation time, enable the adoption of DataOps as a data discipline, and enhance the platform’s flexibility to quickly adapt to changing business needs.
The platform creates and delivers a trusted, holistic, secure, and up-to-date view of any business entity, enriched with operational intelligence, to any consuming application, data lake, or data warehouse. It’s a modular, integrated platform, open to interoperate with an enterprise’s existing data management investments.
At the core of the platform is patented Micro-Database™ technology, which collects, unifies, and stores each business entity’s data (from an enterprise’s disparate data sources – cloud and on-premise) into its own high-performance, encrypted, and distributed Micro-Database. In effect, the Micro-Database stores a specific business entity’s 360-degree view, and keeps it current by syncing to underlying source systems according to user-defined rules.
Here are just some of the new and enhanced core data fabric features of K2View Data Product Platform:
An automated data catalog discovers and visualizes metadata structure, the relationships between data entities managed in the data fabric, and active metadata that represents frequency of access and performance. The result is a graphical, easy way to navigate and search, enabling data teams to find and understand the datasets they need to drive operational and analytical use cases.
Data orchestration tools make it easy to support complex data movement, flows, and transformation in a structured way that reuses business logic, and speeds up implementation –without writing any code.
Dynamic data virtualization tools provide enterprises with complete flexibility to decide which data to virtualize – unified, transformed, and delivered from source to target – and which data to store physically in the data fabric.
Automated Data Services incorporate a no-code/low-code framework for developers to rapidly create, test, debug, govern, and deploy web services that provide secure access to componentized data in the fabric.
Edge integration and deployment enable the platform to integrate data from IOT edge devices, and be deployed in a highly distributed edge architecture, for enhanced performance and security (such as data masking, via data masking tools).
Data Product Platform, with its new core data fabric architecture features, can also be run on data mesh architecture and data hub architecture – and can be deployed on premises, in the cloud (iPaaS), or across hybrid environments.