This topic describes the basic terms used in DataV-Note (smart analytics). Understanding these terms will help you use the product more effectively.
Project
A project is an analysis project. The core of a project is a Notebook analysis document. After a project is created, it can be published as a report or an application.
Analysis unit
An analysis unit is the basic component within an analysis document where you perform analysis. Analysis units include various types, such as Text/Markdown, SQL, Python, visualization, and interactive controls. These units are combined to form a complete analysis document.
Data source
A data source is the source of raw data for visualizations or data analytics. You can connect your own database, such as an RDS MySQL database, to DataV-Note and use it as a data source. After the database is connected, you can analyze its tables in your project.
Project dataset
A project dataset is the intermediate data generated during an analysis. This data is saved in memory or referenced as a view, which greatly improves the performance of subsequent analysis.
Output types for analysis units
View
A standard view. Queries that depend on this view are passed through to the source table.
CachedView
A cached view. The view data is cached locally in DataV-Note, which speeds up queries and reduces the load on the source table.
DataFrame
A Pandas dataset that lets you use Pandas to perform data operations in Python nodes.