Before using DataArts Studio, you must conduct data and business surveys and select an appropriate data governance model.
Then, make the following preparations by referring to this topic:
If you use DataArts Studio for the first time, create a DataArts Studio instance and create a workspace by following the instructions provided in section "Preparations" in the DataArts Studio User Guide. Then you can develop and operate data in the workspace.
Many on-premises data sources are of MySQL, PostgreSQL, HBase, and Hive type. Therefore, you need to make the following preparations:
After the data source is prepared, you can migrate the data source to the data lake by using data integration, and then perform data development, governance, and operations using DataArts Studio.
Before using DataArts Studio, select a cloud service as the data lake. The data lake stores raw data and data generated during data development and is used for subsequent data development, services, and operations. For details on the data lake products supported by DataArts Studio, see Data Sources.
After the data lake is prepared, you can create a data connection to connect DataArts Studio to the data lake and then perform 1 and 2. For details about the operations in 1 and 2, see "Step 2: Preparations" in Getting Started.
Before using DataArts Migration to migrate your data to the cloud, create a destination database in the data lake. According to the implementation process of data lake governance, you are advised to create a database for each of the SDI layer, DWI layer, DWR layer, and DM layer in the data lake to implement hierarchical sharding. Data sharding is a concept involved in DataArts Architecture. You will know more about it during architecture design.
Before using DataArts Migration to migrate your data to the cloud, create a destination table in the SDI layer database of the destination data lake to store raw data. During batch data migration, a destination table can be automatically created for the migration between relational databases and from a relational database to Hive. In this case, you do not need to create the destination table in the destination database in advance.