the data explorer
The data explorer
A data scientist’s missions are, among others, to develop predictive models, to make data understandable and exploitable for the enterprise’s top management, and build machine learning algorithms.
To achieve their missions, collaborators must be able to determine what data is available, which ones they really need, understand the data (context and quality), and finally know how to retrieve them! Zeenea offers the solution and features to fulfill their needs.
The Social Data Explorer for Data Scientists
Zeenea is an enterprise’s metadata search engine; it allows Data Scientists, among other things, to find, identify, and understand data via an intuitive interface.
Intuitive and easy to setup, our metadata management platform will help you face these challenges to able to:
Discover your data
Easily find and retrieve relavant datasets
Our data catalog indexes, and automatically updates, a data set’s knowledge in Zeenea from the storage systems with which it is connected.
In the same way as Google, Data Scientists have access to a search engine to accelerate and simplify the discovery of relevant data sets for their use cases.
Simply type in a keyword, add a few filters, click search to find the needed data sets.
Give meaning to your data assets
Zeenea’s features allow data users, such as Data Scientists, to understand a data set’s context.
Metadata imported automatically or manually entered by the Data Steward in our data catalog allows anyone to verify the relevancy or even the quality of a data set for their use case.
A Data Scientist can also study the relations associated with a data asset with our data lineage feature, a visual representation of the lifecycle of the data.
Improve data knowledge
Collaborate with all employees
We offer a collaborative data catalog that allows Data Scientists to share their knowledge on datasets thanks to our community features.
The different data profiles (CDO, Data Steward or even a Data Analyst) thus participate in the construction and improvement of knowledge of the enterprise’s data assets.
The centralized information in our data catalog allows a tribal knowledge around an enterprise’s data. In fact, sharing information and feedback in our data catalog allows Data Scientists to make better decisions when choosing which datasets to use.