Creating a Graphical View

Create a view to query sources in an intuitive graphical interface. You can drag and drop sources from the Source Browser, join them as appropriate, add other operators to remove or create columns and filter or aggregate data, and specify measures and other aspects of your output structure in the output node.

Prerequisites

To create views, you must have a scoped role that grants you access to a space with the following privileges:

Data Warehouse General (-R------) - To access SAP Datasphere.
Data Warehouse Data Builder (CRUD----) - To create, edit, and delete a graphical view.
Space Files (CRUD----) - To create, read, update, and delete objects in your spaces.

In addition, if you want to use AI features, they must be enabled in your tenant (see Enable SAP Business AI for SAP Datasphere) and you must have the following global privilege:

Data Warehouse AI Consumption (----E---) - To use SAP Business AI features.

The DW Modeler role template, for example, grants these scoped privileges and the DW AI Consumer global role grants the global privilege. For more information, see Privileges and Permissions and Standard Roles Delivered with SAP Datasphere.

Context

If you are comfortable writing SQL code or want to use SQL Script to create your view, you can use the SQL View editor (see Creating an SQL View).

For information about making your data accessible outside SAP Datasphere, see Exposing Data For Consumption.

In addition to working with views in the editor, you can also:

List, create, read, update, and delete them using the datasphere command line interface (see Manage Modeling Objects and Tasks via the Command Line).
Export and import them via the secure Transport app (see Transporting Content Between Tenants).
Export and import them via CSN files (see Importing and Exporting Objects in CSN/JSON Files).

Procedure

In the side navigation area, select  (Data Builder), select a space if necessary, and select New Graphical View to open the editor.
Drag a first source from the Source Browser and drop it into the diagram.

The source is added to the diagram along with an output node, initially entitiled View 1, which represents the final output structure of the view.

For more information, see Add a Source to a Graphical View.
[optional] Drag additional sources from the Source Browser and drop them on your source to create a join or union.
For more information, see Create a Join in a Graphical View and Create a Union in a Graphical View.

Click a node in the diagram to display tools for creating operators and performing other actions:

Tools	Description
 (Filter)	Add a Filter node to filter your data with an SQL expression. For more information, see Filter Data in a Graphical View.
 (Rename/Exclude Columns)	Add a Projection node to rename, reorder, or exclude columns. For more information, see Reorder, Rename, and Exclude Columns in a Graphical View.
 (Calculated Columns)	Add a Calculated Columns node to create new columns and define calculations in them. For more information, see Create a Calculated Column in a Graphical View or SAP HANA SQL and System Views Reference.
 (Aggregation)	Add an Aggregation node to perform `SUM`, `COUNT`, `MIN`, and `MAX` calculations. For more information, see Aggregate Data in a Graphical View.
 (Join Suggestion)	Create a join from a list of Related Entities that is populated based on the presence of associations between the current source and other artifacts.
 (Preview Data)	Preview the data output by the selected diagram node in the Data Preview panel (see Viewing Object Data). Note Users with the DW Viewer role cannot preview data if the Expose for Consumption switch is disabled and, if the switch is enabled, can only preview data in the output node. For more information, see Privileges by App, Tool, Object, and Task. You can preview the SQL generated for the node by clicking the Preview SQL button in the panel or by clicking  Export and selecting Preview SQL. Click Copy to copy the SQL code for pasting into the SQL View editor or elsewhere.
 (Impact and Lineage Analysis)	Open the Impact and Lineage Analysis diagram. This diagram enables you to understand the lineage and impacts of the selected object. (see Impact and Lineage Analysis.)
 (Runtime Metrics)	Open the Runtime Metrics tool to analyze the performance of your view. This tool also provides the option to directly generate and download an Explain Plan or execute View Analyzer to improve your view performance. (see Analyzing View Performance.)
 (Open in New Tab)	Open the object in its own editor in a new tab.

Click the output node to show the view's properties in the side panel. Enter the following properties as appropriate:

Property	Description
Business Name	Enter a descriptive name to help users identify the object. This name can be changed at any time.
Technical Name	Displays the name used in scripts and code, synchronized by default with the Business Name. To override the default technical name, enter a new one in the field. Technical names can contain only alphanumeric characters and underscores. Note Once the object is saved, the technical name can no longer be modified.
Package	Select the package to which the object belongs. Packages are used to group related objects in order to facilitate their transport between tenants. Note Once a package is selected, it cannot be changed here. Only a user with the DW Space Administrator role (or equivalent privileges) can modify a package assignment in the Packages editor. For more information, see Creating Packages to Export.
Semantic Usage	Select the way your entity should be used for data modeling purposes. Choose from the following: Fact - Contains one or more measures and attributes. A fact typically has associations pointing to one or more dimensions and is consumed by analytic models (see Create a Fact to Contain Measurable Data). Dimension - Contains attributes containing master data like a product list or store directory, and supporting hierarchies (see Create a Dimension to Categorize Data). Hierarchy - Contains attributes defining a parent-child hierarchy (see Create an External Hierarchy for Drill-Down). Hierarchy with Directory - Contains one or more parent-child hierarchies (see Create a Hierarchy with Directory). Text - Contains attributes used to provide textual content in one or more languages (see Create a Text Entity for Attribute Translation). Relational Dataset - [default] Contains columns with no specific analytical purpose. Analytical Dataset (Deprecated) - Use Fact instead (see Analytical Datasets (Deprecated).
Dimension Type	[dimensions only] Select whether your dimension is Standard or Fiscal Time. For Fiscal Time dimensions, see Create a Fiscal Time Dimension.
Expose for Consumption	Enable this option to make the view available for consumption outside SAP Datasphere via OData or ODBC/JDBC. This option is not required if you want to expose your data through an analytic model (see Creating an Analytic Model). For an overview about making your data accessible outside SAP Datasphere, see Exposing Data For Consumption.
Run in Analytical Mode	Enable this option to send the `USE_OLAP_PLAN` hint to the SQL optimizer. This may improve view performance, particularly if a union is performed. It is only available if Expose for Consumption is enabled. For more information, see HINT Details in the SAP HANA Cloud, SAP HANA Database SQL Reference Guide.
Status	[read-only] Displays the deployment and error status of the object. For more information, see Saving and Deploying Objects.
Deployed On	[read-only] Displays the date and time of the last deployment.
Data Validation Status	Displays the status of the last data validation. Click the button to open the Data Validation panel (see Validating View Data).
Validated On	[read-only] Displays the date and time of the last data validation.

Based on the Semantic Usage of your entity, review and modify its Columns, Attributes, and/or Measures:
- Fact - Review the lists of measures and attributes (see Create a Fact to Contain Measurable Data).
- Dimension - Review the list of attributes (see Create a Dimension to Categorize Data).
- Hierarchy - Define the parent and child columns (see Create an External Hierarchy for Drill-Down).
- Hierarchy with Directory - Define all the necessary attributes and settings (see Create a Hierarchy with Directory).
- Text - Review the list of attributes (see Create a Text Entity for Attribute Translation).
- Relational Dataset - Review the list of columns (see Columns).
- Analytical Dataset (Deprecated) - Use Fact instead (see Analytical Datasets (Deprecated).
Note

If a column contains Personal Data or Sensitive Personal Data from a data product, then it is tagged accordingly, and its parent object also displays the appropriate tag (see Modeling with Personal Data).
Complete or consult other sections as appropriate:
- Input Parameters - Create input parameters to require the user to enter a value for use in calculated column, filter, and aggregation nodes (see Create an Input Parameter in a Graphical View).
- Data Persistence - Persist the view data to improve performance (see Persist Data in a Graphical or SQL View).
- Associations - Create associations to other entities (see Create an Association to Define a Semantic Relationship Between Entities).
- Data Access Controls - Add data access controls to apply row-based security and control access to individual rows based on various criteria (see Securing Data with Data Access Controls).
- Business Purpose - Provide a description, purpose, contacts, and tags to help other users understand your entity.
- Dependent Objects - If your entity is used as a source or association target for other entities, then they are listed here (see Review the Objects That Depend on Your Table or View).
Click  (Save) Save to save your entity or click  (Deploy) to save and deploy it immediately.
For more information, see Saving and Deploying Objects.

The tools in the editor toolbar help you work with your object throughout its lifecycle:

Tool	Description
 (Save)	Save your changes to the design-time repository. You can use Save As to create a copy of the object. See Saving and Deploying Objects.
 (Deploy)	Deploy your changes to make them available in the run-time environment. See Saving and Deploying Objects.
 (Share)	Share the object to other spaces. See Sharing Entities and Task Chains to Other Spaces.
 (Source Browser)	Show the Source Browser panel to drag sources into the editor. See Using the Source Browser.
 (Preview Data)	Open the Data Preview panel to preview data in the selected diagram node. See Viewing Object Data.
 (Undo) /  (Redo)	Revert the last change to the object or redo a change you have previously undone.
 (Export)	Export the object to a CSN/JSON file. See Exporting Objects to a CSN/JSON File.
 (Edit Custom CSN Annotations)	Work with custom CSN annotations that are not otherwise supported by the interface. See Edit Custom CSN Annotations in a View or Table.
 (Impact and Lineage Analysis)	Open the Impact and Lineage Analysis graph for the object. See Impact and Lineage Analysis.
 (Generate OData Request)	Open the Generate OData Request dialog to prepare access to the OData API. See Consuming Data via the OData API.
 (Runtime Metrics)	Open the Runtime Metrics tool to analyze the performance of your view. This tool also provides the option to directly generate and download an Explain Plan or execute View Analyzer to improve your view performance. See Analyzing View Performance.
 (Generate)	Open the AI-assisted generation menu: Generate Semantics - Identify the semantic usage of your entity and the semantic types of its columns (see Generate Semantic Information).
Versions	Open the Version History dialog for the object. See Reviewing and Restoring Object Versions.
Details	Toggles the display of the Properties panel.
 (Open Data Pipeline Analyzer)	The Data Pipeline Analyzer helps you view and analyze errors, warnings, or data discrepancies for a selected object, so that you can understand the point of data transfer failure. This tool is useful for identifying and resolving data transfer failures, ensuring efficient data flow management and troubleshooting within complex data models. See Data Pipeline Analyzer