Dave Chiou
In Gartner's 2020 research paper: Demystifying the Data Fabric, Gartner discusses that the core of the data fabric is able to consolidate many diverse data sources in an efficient manner by allowing trusted data to be delivered from all relevant data sources to all relevant data consumers through one common layer.
Easily maintaining a data fabric that changes and evolves is critical to a successful implementation. Like self-driving cars, modern data fabric designs enable dynamic machine learning to look at query patterns and make recommendations to keep running well. A data fabric needs to easily detect and manage changes in source systems along with handling any future migrations without impacting your data consumers and applications.
Watch on-demand this webinar to learn:
- How to connect, model and delivery data in the data fabric
- How to support different integration styles that best supports the data fabric
- How to feed query usage history to the recommendation engine
- How to create, load and selectively materialize data for accelerating query performance.
- How to detect and handle source metadata/schema changes.
- How to migrate data sources in the data fabric without impacting users and applications.
