Data Hub can be improved with more automation; there are some inbuilt automations, such as documenting definitions of data elements using AI, which is useful. I wonder if it can automate the classification exercise, possibly using AI to auto-classify PII direct and indirect items.
The impact is very positive, and there are many benefits for us using Data Hub because it was easier to make data governance, create centralized metadata management, improve data discoverability, and manage data in general. The areas for improvement, in my opinion, are the initial setup and configuration that can be complex without prior experience, especially in large-scale environments. User experience for non-technical users could be further simplified, particularly around advanced metadata concepts. The out-of-the-box governance workflow, for example, approvals and certification, could be more prescriptive for customers at early maturity stages. Data Hub can be improved in the initial setup and configuration that is somewhat complex, and also in operational monitoring that could benefit from more native dashboards and alerts. However, these are not blockers, but areas where additional guidance or product enhancement would further accelerate adoption.
The product cannot be improved in just one area. There are no points in support or documentation that require improvement. There are no improvements needed for Acryl Data that I have not mentioned yet.
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...
Data Hub can be improved with more automation; there are some inbuilt automations, such as documenting definitions of data elements using AI, which is useful. I wonder if it can automate the classification exercise, possibly using AI to auto-classify PII direct and indirect items.
The impact is very positive, and there are many benefits for us using Data Hub because it was easier to make data governance, create centralized metadata management, improve data discoverability, and manage data in general. The areas for improvement, in my opinion, are the initial setup and configuration that can be complex without prior experience, especially in large-scale environments. User experience for non-technical users could be further simplified, particularly around advanced metadata concepts. The out-of-the-box governance workflow, for example, approvals and certification, could be more prescriptive for customers at early maturity stages. Data Hub can be improved in the initial setup and configuration that is somewhat complex, and also in operational monitoring that could benefit from more native dashboards and alerts. However, these are not blockers, but areas where additional guidance or product enhancement would further accelerate adoption.
I do not have comments on how Acryl Data can be improved.
The product cannot be improved in just one area. There are no points in support or documentation that require improvement. There are no improvements needed for Acryl Data that I have not mentioned yet.