What is our primary use case?
data.world Enterprise serves as an enterprise data catalog that makes data assets across the organization findable and understandable. We use it for data governance to enforce policies, manage access, track stewardship, and maintain audit trails. Additionally, we utilize it for metadata management to understand metadata for different data sets.
A specific example of how my team uses data.world Enterprise is to obtain information about tracking lineage and gaining more business context for our data. We focus on understanding who owns the data, the state of use the data is in, and what stage of processing it is currently at, which helps us understand how best to use the data by gaining more information about the type of data, its owner, and its current state.
I can give a specific example about a workflow that occurred earlier in the year prior to data.world Enterprise being rolled out in our organization when we had data silos. We had to rely on the data engineers to provide responses and pass on information about how the data is stored, what the data is about, who owns the data, and the permissions required to access it. However, since deploying data.world Enterprise, analysts could work independently without relying on data engineers to share institutional knowledge, with all the data catalog surfacing in a searchable context-rich environment where lineage, ownership, and certification status are visible at a glance.
What is most valuable?
data.world Enterprise offers three best features that I find most valuable. The first is the knowledge graph foundation, which is heavily built on graph technology that makes its function more efficient. The second is the Eureka Explorer, a data discovery and lineage visualization tool for navigating asset relationships. The third most useful feature is Archie, the embedded built-in AI assistant that combines the knowledge graph and modern LLM to ensure users interact conversationally with the catalog, receive guided support, and most essentially get accurate information about the data stored on the server systems.
Archie has changed our workflow significantly because it pulls data from the data already stored on the servers. Archie is very reliable and able to provide accurate answers without hallucination, which has been a game-changer for our team. We can simply interface with Archie and obtain the information we need without having to search different catalogs ourselves, just asking about this or that, and it provides the answer immediately. Then we investigate the data and the dataset to ensure it is the right one to use.
With Archie, you can also get guided support, especially concerning catalog management tasks, even after identifying the dataset to use. This helps find precise information in databases without writing extensive queries on different datasets. Archie can bring out the actual data points you are looking for, enabling you to work with that effectively.
data.world Enterprise has had a positive impact on our organization by breaking down data silos where all data assets are visible to all analysts and searchable from one place. It further reduces dependence on individual data experts or single sources of knowledge. It also accelerates onboarding, so when a new analyst joins, they no longer have long sessions walking around the database management system. They can simply ask data.world Enterprise for information regarding permissions and asset details, making onboarding easier.
Previously, it would take up to three weeks to onboard a new analyst, but now within five working days, we can complete the onboarding process. That is a huge reduction in time. Additionally, for analysts, there is a significant reduction in time spent locating and vetting datasets before analysis can begin. With data.world Enterprise, you can immediately see the state, health, and quality of the data in the database, minimizing the need for extensive querying and data preparation.
What needs improvement?
The first improvement I would like for data.world Enterprise is an improvement in communication with users. Most times, new versions roll out without prior information to users, and even though frequent updates respond to issues, they often introduce new bugs. It would be beneficial to send out notifications to users whenever an update is coming, either via email or in-app, so that they can prepare and expect changes. I also find that some areas of the product interface are overly complex, and interface customization needs improvement for users to choose where buttons should be and the layout they prefer.
Another improvement needed is the absence of a bulk edit feature in the platform itself. For example, when searching for data and needing to do some edits, you cannot do bulk edits within data.world Enterprise. Instead, you have to export and make your changes in a Python or SQL environment, or use Excel to validate and edit before importing the dataset back for analysis. If data.world Enterprise could incorporate a data-wrangling tool on its service, allowing changes to be made directly, that would be a great improvement.
For how long have I used the solution?
I have been working in my current field for four years. I have been using data.world Enterprise for the last five months. It was rolled out in February of this year, and as of July, that is five months of usage.
What other advice do I have?
Archie has changed our workflow significantly because it pulls data from the data already stored on the servers. Archie is very reliable and able to provide accurate answers without hallucination, which has been a game-changer for our team. We can simply interface with Archie and obtain the information we need without having to search different catalogs ourselves. Then we investigate the data and the dataset to ensure it is the right one to use.
With Archie, you can also get guided support, especially concerning catalog management tasks, even after identifying the dataset to use. This helps find precise information in databases without writing extensive queries on different datasets. Archie can bring out the actual data points you are looking for, enabling you to work with that effectively.
data.world Enterprise has had a positive impact on our organization by breaking down data silos where all data assets are visible to all analysts and searchable from one place. It further reduces dependence on individual data experts or single sources of knowledge. It also accelerates onboarding, so when a new analyst joins, they no longer have long sessions walking around the database management system. They can simply ask data.world Enterprise for information regarding permissions and asset details, making onboarding easier.
Previously, it would take up to three weeks to onboard a new analyst, but now within five working days, we can complete the onboarding process. That is a huge reduction in time. Additionally, for analysts, there is a significant reduction in time spent locating and vetting datasets before analysis can begin. With data.world Enterprise, you can immediately see the state, health, and quality of the data in the database, minimizing the need for extensive querying and data preparation.
My advice for others looking into using data.world Enterprise is to focus on catalog adoption first. The platform is only as powerful as the quality of data documented in it. There should be dedicated personnel to verify the completeness and accuracy of data before rolling out data.world Enterprise. Also, ensure there is a clear scope of coverage, loading the most important datasets first and expanding coverage gradually. Finally, I advise evaluating other options before choosing data.world Enterprise due to its high cost. The basic option is approximately ninety thousand dollars per year. I would rate this solution a seven out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
