Create a Data Source

A Data Source is an entity that holds the properties (location and access credentials) of the source of your data.

  • If you integrate data from data warehouses, a Data Source stores the properties of a data warehouse and the prefix for the Output Stage if the Output Stage is used.
  • If you integrate data from object storage services, a Data Source stores the properties of an object storage service.

For more information, see Direct Data Distribution from Data Warehouses and Object Storage Services.

You can also create Data Sources via the API.

Contents:

Create a Data Source for a BigQuery Project

GoodData supports using a Google service account key file to integrate your BigQuery dataset with the GoodData workspace.

When creating a data source for a BigQuery project, you have two options:

  • upload the service account key file
  • fill in all the connection details manually

For more information, see GoodData-BigQuery Integration Details.

Steps:

  1. From the Data Integration Console (see Accessing Data Integration Console), click the Data sources tab.
  2. Click Add Data Source in the left pane, and select Google BigQuery.
  3. When prompted, do one of the following:
    • Upload the Google service account key file.


      Note: Ensure that you fill in the Dataset name.
    • Alternatively, click Connect Manually and enter all the details manually.
  4. Enter the name of the Data Source.
    The alias will be automatically generated from the name. You can update it, if needed.
  5. (Optional) If you plan to use the Output Stage (see Direct Data Distribution from Data Warehouses and Object Storage Services), enter the prefix that will be used for the Output Stage tables and views.
  6. Click Test connection.
    If the connection succeeds, the confirmation message appears.
  7. Click Save.
    The Data Source is created. The screen with the connection details opens.

Create a Data Source for a Redshift Cluster

Steps:

  1. From the Data Integration Console (see Accessing Data Integration Console), click the Data sources tab.
  2. Click Add Data Source in the left pane, and select Amazon Redshift.
    The connection parameter screen appears.
  3. Enter the name of the Data Source.
    The alias will be automatically generated from the name. You can update it, if needed.
  4. Enter the details of your connection to the Redshift cluster.
  5. (Optional) If you plan to use the Output Stage (see Direct Data Distribution from Data Warehouses and Object Storage Services), enter the prefix that will be used for the Output Stage tables and views.
  6. Click Test connection.
    If the connection succeeds, the confirmation message appears.
  7. Click Save.
    The Data Source is created. The screen with the connection details opens.

Create a Data Source for a Snowflake Instance

Steps:

  1. From the Data Integration Console (see Accessing Data Integration Console), click the Data sources tab.
  2. Click Add Data Source in the left pane, and select Snowflake.
    The connection parameter screen appears.
  3. Enter the name of the Data Source.
    The alias will be automatically generated from the name. You can update it, if needed.
  4. Enter the details of your connection to the Snowflake instance.
  5. (Optional) If you plan to use the Output Stage (see Direct Data Distribution from Data Warehouses and Object Storage Services), enter the prefix that will be used for the Output Stage tables and views.
  6. Click Test connection.
    If the connection succeeds, the confirmation message appears.
  7. Click Save.
    The Data Source is created. The screen with the connection details opens.

Create a Data Source for an S3 Bucket

Steps:

  1. From the Data Integration Console (see Accessing Data Integration Console), click the Data sources tab.
  2. Click Add Data Source in the left pane, and select Amazon S3.
    The connection parameter screen appears.
  3. Enter the name of the Data Source.
    The alias will be automatically generated from the name. You can update it, if needed.
  4. Enter the path to your S3 bucket, the access key, and the secret key.
  5. (Optional) Enter the region and select the Server side encryption check box if your S3 location supports these options.
  6. Click Test connection.
    If the connection succeeds, the confirmation message appears.
  7. Click Save.
    The Data Source is created. The screen with the connection details opens.

Create a PostgreSQL Data Source

Steps:

  1. From the Data Integration Console (see Accessing Data Integration Console), click the Data sources tab.
  2. Click Add Data Source in the left pane, and select PostgreSQL.
    The connection parameter screen appears.
  3. Enter the name of the Data Source.
    The alias will be automatically generated from the name. You can update it, if needed.
  4. Enter the parameters.
  5. Click Save.
    The Data Source is created. The screen with the connection details opens.

Create a Generic Data Source

Generic Data Sources (Data Sources for an arbitrary location) are used in more complex scenarios. For example, when you need to specify access credentials for an ADS instance or a WebDAV location and then reference them from other components (see Reuse Parameters in Multiple Data Loading Processes).

Steps:

  1. From the Data Integration Console (see Accessing Data Integration Console), click the Data sources tab.
  2. Click Add Data Source in the left pane, and select Generic data source.
    The connection parameter screen appears.
  3. Enter the name of the Data Source.
    The alias will be automatically generated from the name. You can update it, if needed.
  4. Enter the parameters.
    You can add regular parameters and secure parameters. Use secure parameters for passing in sensitive data, such as passwords and secret keys. These parameter values are encrypted and do not appear in clear-text form in any GUI, API responses, or log entries.
    Before saving the Data Source, use the show value check-box to display the value of a secure parameter for review purposes. When the Data Source is saved, secure parameter values are hidden.
  5. Click Save.
    The Data Source is created. The screen with the connection details opens.

Create an Agile Data Warehouse Service Data Source

If you have the ADS export add-on, you can create an ADS Data Source to export data from your ADS Instance. For more information on the ADS export add-on, see Exporting Data from Data Warehouse

This Data Source is unavailable as a selection when the enableADSDataSource platform setting is set to false. For more information on how to configure platform settings, see Configure Various Features via Platform Settings.

Only the creator the ADS Data Source can edit the data source after it is created.

Steps:

  1. From the Data Integration Console (see Accessing Data Integration Console), click the Data sources tab.
  2. Click Add Data Source in the left pane, and select Agile Data Warehouse Service Data Source.
    The connection parameter screen appears.
  3. Enter the name of the Data Source.
    The alias will be automatically generated from the name and can be updated later if needed.
  4. Select the ADS instance you want to export. Only ADS instances assigned to your domain will appear.
  5. Specify the prefix for the tables or views that you want to export.
  6. Select exportable if you want to use this data source for export.
  7. Click Save.
    The Data Source is created. The screen with the connection details opens.
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