Overview

Metadata is data about data. Metadata streamlines source data, data warehouses, and data applications, and records the entire process from data generation to data consumption. Metadata mainly refers to model definitions in the data warehouse and mappings between layers. It also describes the monitoring data status of the data warehouse and running status of ETL tasks. In the data warehouse system, metadata helps data warehouse administrators and developers easily locate the data they are looking for, improving the efficiency of data management and development.

In DataArts Studio, metadata may be used to describe the attributes of data (such as the data connection, type, name, and size) or other related information of data (such as the data owner, tag, category, and security level).

Metadata is classified into technical metadata and business metadata by function.

• Technical metadata is data that stores technical details of a data warehouse system and is used to develop and manage data warehouses. In DataArts Studio, technical metadata is technical assets, including databases, data tables, and data volume and their details.
• Business metadata describes data in a data warehouse from the business perspective. It provides a semantic layer between users and actual systems, enabling business personnel who do not understand computer technologies to understand data in the data warehouse. In DataArts Studio, business metadata includes logical assets and metric assets. Business assets include business objects, logical entities, and business attributes and their details. Metric assets include business metrics and their details.

Technical metadata in DataArts Studio are obtained through metadata collection tasks. You can view metadata on the Data Map page only after you have created and run a metadata collection task.