MarkovML Datasets may be segmented to distinguish data used to train, test, or validate a model.
A **Dataset** is a collection of examples. Each example, in turn, comprises one or more **variables** and possibly a **label** or **target**. When you register your datasets with MarkovML, we analyze your data and help you to understand key characteristics such as distributions, column correlations, empty value frequency, and more.
A single MarkovML Dataset can be **segmented** or **unsegmented**. ML engineers frequently divide datasets into segments to train, test, and/or validate a model. MarkovML allows you to specify different dataset segments and provides insights into how your **train**, **test**, and **validate** segments compare.
Data Family is a collection of datasets
#### Data Family
To help keep your datasets organized, each dataset you register with MarkovML is associated with a *data family*. A **data family** is a set of one or more Datasets that share a similar schema. Organizing your datasets into data families makes it much easier to locate a particular dataset when needed.
