The Business Glossary feature is quite useful. It helps clarify terminology across the team, which is essential for large projects.
The learning curve is steep. Despite its potential, getting teams to adopt it fully has been challenging.
It does assist in creating a shared understanding of data architecture, but the overall experience hasn't improved our workflow as we hoped.
The collaborative tools are a big plus, making it easier for teams to work together on data projects.
The documentation could be much better. Finding answers to specific issues is often a challenge.
It helps align our data strategy with business needs, but there are still gaps in execution that need addressing.
I love the integration options. It allows for a flexible setup that can be tailored to different data needs.
Sometimes, the performance can lag when dealing with large datasets, which can be frustrating.
It has made our data governance processes smoother, enabling better compliance and oversight, which is crucial for our industry.
I appreciate the idea behind Ellie.ai's data visualization features. It has potential for teams that need to visualize complex data models.
The interface feels clunky and outdated. It takes a lot of time to navigate through the features, which detracts from productivity.
While it claims to simplify data management, I've found it quite the opposite. Integration with existing tools is not seamless, which creates more hurdles than it solves.
Ellie.ai's focus on data architecture is impressive. The tools provided for data modeling are robust and well thought out.
There are occasional bugs that disrupt workflow, which can be annoying.
It significantly improves our ability to manage complex data structures and enhances communication within teams.
The concept of having everything integrated in one place is appealing.
It is not user-friendly at all. I often find myself lost within the features.
While it attempts to streamline data processes, it mostly adds complexity rather than solving our existing issues.
