The properties on the Details tab allow you to name the data view, add data stores, and select a primary data store if multiple stores are used.
- Name - Type a name for your data view.
- Description - Optionally, enter a description for your data view. If you enter a description, this will be displayed as a tooltip when you hover over the data view in the Pipelines view.
- Data Store - Click the Add button to add data stores.
- Primary Data Store - Select a primary data store if multiple data stores are used.
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Storage Type - Select how the data view's data is stored behind the scenes. The option that you choose essentially affects how quickly dashboards that use the data view will render. Choose from:
- Regular Performance - Data views that use regular performance will have their data stored in traditional hard drives. As such, dashboards that use regular performance data views perform slightly slower than dashboards that use high performance data views. For this reason, it is recommended that regular performance is used for dashboards that are accessed occasionally. For example, if you have dashboards that drill down to a very detailed level of information that are used infrequently, you would want to set them to regular performance.
- High Performance - Data views that use high performance will have their data stored in solid state hard drives. As such, dashboards that use high performance data views perform slightly faster than dashboards that use regular performance data views. For this reason, it is recommended that high performance is used for dashboards that are accessed frequently. For example, if you have dashboards that contain summary information and are used frequently, you would want to set them to high performance, so that they always render quickly.
- Big Data - On the cloud version of the product, this setting can be used to query Data Views based on Amazon Athena. On the enterprise version of the product, this setting can be used to query Data Views based on Hive/Impala. This setting is suitable for use with large amounts of data where using Amazon RedShift on the cloud or Vertica on the enterprise could be cost prohibitive. Checking this box results in a file based Data View that trades off performance for lower cost.
- Low Data - A low volume data view is backed by the standard Postgres database (for example, the one used in case stores). Switching a data view storage type to low volume from high or regular performance incurs a migration process upon save, this moves the data from Redshift/Vertica/Synapse to Postgres and vice-versa.
Note: If you are running Data360 DQ+ in Azure, the only available Storage Type is High Performance. - Table Name Prefix - Optionally create a prefix of up to thirty characters that will be added to the Data View's underlying, unique name. Doing so can allow you to search for the Data View by name, when querying the database that retains Data View information, with an external tool. Without a Table Name Prefix, a Data View's name will instead just be a non-meaningful, alphanumeric string. Adding a Table Name Prefix can make searching for the Data View easier.