Data warehouse layering

Built-in layers

DataWorks provides five built-in layers by default: Operational Data Store (ODS) , Dimension (DIM) , Data Warehouse Detail (DWD) , Data Warehouse Summary (DWS) , and Application Data Service (ADS) .

Each layer serves a specific function:

Custom layers

Go to the Data Layer page to view the built-in data warehouse layers. You can switch between Tiled Display and Hierarchy Display to adjust the page layout.

If the built-in layers do not meet your requirements, you can create custom layers:

Configure data warehouse layer checkers

A data warehouse layer checker enforces naming conventions for models and metrics. When you create an object, the checker can automatically generate its name, which makes the published physical table name intuitive and easy to understand.

1. Click a layer to go to its details page.

2. In the Checker Management section, click Create Rule and select Create Rule for Model or Create Rule for Metric .

3. The following tables describe the checker parameters.

   Model rule

   Parameter	Description
   Rule Name	The name of the checker rule.
   Rule Type	Model rule: Defaults to Table Name (the English table name). When you create a model in Dimensional Modeling , you can select the corresponding checker to automatically generate a table name.
   Rule Definition	Defines the naming convention for the data model. This rule is used to check model names within the layer in Dimensional Modeling. Model rule: Enter a prefix for the table to validate against. For example, if the data warehouse layer requires table names to start with dim, you can enter dim. You can also click the icon to define the rule by using elements such as business category abbreviation, data domain abbreviation, data mart abbreviation, or subject area abbreviation. You can freely combine these elements. The following are recommended naming conventions: Dimension (DIM): dim_{business_category}_{data_domain}_{custom_content}_{storage_policy} Data Warehouse Detail (DWD): dwd_{business_category}_{data_domain}_{business_process}_{custom_content}_{storage_policy} Data Warehouse Summary (DWS): dws_{business_category}_{data_domain}_{custom_content}_{time_period} Application Data Service (ADS): ads_{business_category}_{data_mart}_{subject_area}_{custom_content}_{time_period}
   Description	A description of the checker.

   Metric rule

   Parameter	Description
   Rule Name	The name of the checker rule.
   Rule Type	Metric rule: Can be configured for Display Name or Abbreviation. When you create a metric, the system automatically generates a name for the derived metric based on the specified default rule.
   Rule Definition	Defines the naming convention for metrics. This rule is used to check metric names within the layer in Data Metrics. Metric rule: Define the rule by selecting modifiers, an atomic metric, and a statistical period. You can combine these elements in any order.
   Description	A description of the checker.

4. Set a default checker.

   In the Default Rule section above the checker list, you can set a default checker for models or metrics. If you do not explicitly specify a rule when creating a model or metric, the system uses the default checker to automatically generate its name.

5. Understand strong and weak rules.

   1. Weak Rule: When a naming checker is set as a Weak Rule, its naming convention is treated as a recommendation. You can ignore the rule and still create the model or metric successfully with a custom name.

   2. Strong Rule: When a naming checker is set as a Strong Rule, you must follow its naming convention to create a model or metric. Otherwise, you cannot save the model or metric.

Use checkers

1. Use checkers in Dimensional Modeling or Data Metrics.

   1. Dimensional Modeling:

      1. Auto-generate table name: When you create a logical model, you can select a checker in the Naming Rule field. The system automatically suggests a Table Name for the table based on the checker rule.

      2. Validate table name: When you create or edit a table name without selecting a checker, the system validates the name that you entered against the checker rules when you save the logical model.

      3. If multiple checkers exist, the validation passes as long as the name conforms to any one of them.

   2. Data Metric:

      1. Auto-generate metric name: When you create a Derived Metric, select a Period, Modifier, and an Atomic Metric, and then click Intelligent Recommendation. The system automatically generates both a display name and an abbreviation based on the Default Rule.

      2. Validate metric name: When you create or edit the Abbreviation and Display Name of a metric, the system automatically checks whether the names conform to the checker rules when you save the metric.

      3. If multiple checkers exist, the validation passes as long as the name conforms to any one of them.

2. Manually Start Check and View Results .

   After you configure a checker, click Start Check to verify that the data model names in the current layer conform to the naming conventions. You can then use the results to correct any non-compliant models.

   Note

   • The Start Check function is not supported for metric rules.

   • The check operation runs only for enabled checkers.

   • A new checker is enabled by default. If you do not need to use a checker, you can disable it to prevent it from running checks.

   After the check is complete, click View Results to review the results.