We adopted Data Hub in the context of a large enterprise customer operating in a regulated industry with a strong focus on data governance, data discoverability, and ownership clarity across multiple cloud-native platforms. The solution was deployed on AWS, and the main business problem was the lack of a centralized, reliable view of data assets, including poor data discoverability, unclear data ownership and stewardship, limited lineage visibility across ingestion and transformation layers, and high dependency on tribal knowledge held by a few individuals. Data Hub was selected as an enterprise data catalog and metadata backbone with the goal of enabling both technical teams and business users to easily understand, trust, and reuse data. We used Data Hub to create very good data discoverability, assign data ownership and stewardship, improve data quality processes, and establish good data governance for our customer in terms of data catalog, data lineage, and metadata management in general.
My main use case for Acryl Data is to extract insights from customer data. I use Acryl Data for a project in order to identify all the customers and find out which customer buys a lot of items.
Metadata Management streamlines data organization by standardizing and defining the data's context within a system, improving data governance and usability. Data-driven organizations require efficient Metadata Management to ensure data integrity and accessibility. By implementing this system, enterprises can maintain consistency across data assets, enabling seamless data interoperability and better decision-making processes. Responsible for facilitating the discovery, management, and...
We adopted Data Hub in the context of a large enterprise customer operating in a regulated industry with a strong focus on data governance, data discoverability, and ownership clarity across multiple cloud-native platforms. The solution was deployed on AWS, and the main business problem was the lack of a centralized, reliable view of data assets, including poor data discoverability, unclear data ownership and stewardship, limited lineage visibility across ingestion and transformation layers, and high dependency on tribal knowledge held by a few individuals. Data Hub was selected as an enterprise data catalog and metadata backbone with the goal of enabling both technical teams and business users to easily understand, trust, and reuse data. We used Data Hub to create very good data discoverability, assign data ownership and stewardship, improve data quality processes, and establish good data governance for our customer in terms of data catalog, data lineage, and metadata management in general.
My main use case for Acryl Data is analytics.
My main use case for Acryl Data is to extract insights from customer data. I use Acryl Data for a project in order to identify all the customers and find out which customer buys a lot of items.