As a data scientist, your goal is to build, train or apply data models with the highest predictive power to forecast business outcomes. You know the secret to a great model: high quality data. You key challenge is to locate trustworthy high quality data, so you can focus on the core of your work.
Find the data you need
Trust the data you use
Collaborate with your peers
You struggle when it it comes to finding and understanding the data assets you need. You spend 80% of your time grappling with questions such as "What does this field name mean? Can this data table be trusted? Who can I ask if I have a question about the data?".
You're unsure of the source of data assets, making it hard to know whether you can trust them when building your models.
When building models, you often repeat preliminary analysis that have already been performed by some of your peers. This costs time and processing power.
Find the data you need. With Castor's search and documentation features, spend 70% less time looking for data. Instead, spend your time analyzing data to drive business performance.
Trust the data you use. In less than a minute, identify the source and the owner of a dataset. This adds a layer of explainability when you report your findings to business users.
Collaborate with your peers. Never repeat the work of others. Castor’s out-of-the-box collaborative features, like chat and query history, make it simple to build on the work of your colleagues.
Castor does not access data itself. We only connect to metadata (schema, table, column names, etc). In addition, we are committed to security and focused on keeping you and your metadata safe. Castor follows industry-leading security standards.
