Introducing data fabric architecture and how it can help organizations in the goal of achieving comprehensive data agility and reliability despite legacy systems and siloed data sources.
In a webinar titled Moving to a Data Fabric: Key Challenges and Enabling Technologies, hosted by TimeXtender and Acceldata, the idea of data fabric is plainly unpacked by hashing out its complexities and potentials.
Data fabric architecture combines metadata management, active metadata, knowledge graphs, semantics & machine learning in several ways to make data integration pipelines better across both operational and analytics use cases.
Though there is no one-vendor solution, TimeXtender’s Unified Metadata Framework offers a thorough path emphasising seamless integration and automation to successfully solve the critical integration complexities.
Acceldata stressed that data quality is a core pillar for an effective data fabric solution perspective. Highlighting the importance of data observability from ingestion to processing,
Acceldata emphasized its significance in maintaining data accuracy and trustworthiness, and operational visibility while optimizing performance and cost management.
Data fabric adoption helps to address some of these challenges as it provides a way for organizations to build data services with the agility, and confidence required in supporting the pace of innovation necessary to achieve business goals.
The webinar provides some useful details for those wanting a deep dive into such complexities in the context of the best practices followed for data fabric adoption and implementation.
Get the full details by visiting here.
