Data Studio Settings

This topic explains the Data Studio settings on the Data Studio tool.

This settings on the Data Studio navigation menu and the Data studio overview page enables you to use the associated Cloud Service, configure AI profile,configure SMTP and create Vector Indexes.

This helps in defining the data during the load. This setting sets a variety of general preferences like setting default credentials to define the data you load, configure SMTP for data sharing, configure AI profile and configure Marketplace cloud link access.

Integration of Slack with Data Studio bridges the gap between real time collaboration between various team members in staying informed and making correct decisions.

To set the Data Studio Settings, on the General tab of the wizard, specify the email address to configure your profile for Marketplace and Sharing.

On the Cloud Services tab of the wizard, under Cloud Object Store Access, specify the following field values:

• OCI Credential: Selecting an OCI credential enables you to discover the OCI buckets. Click + to create OCI Credentials.
• OCI Compartment: This drop-down field lists the buckets present in your compartment for loading and linking from Oracle cloud services. If you select any other cloud service provider apart from Oracle, this field displays None by default.
• AWS Credential: Selecting an AWS credential in Data Studio Settings enables you to discover the S3 buckets. Click + to create credentials for Amazon S3 cloud storage.
• Azure Credential: Selecting an Azure credential in preferences enables you to discover the Azure BLOB storage. Click + to create credentials for Microsoft Azure BLOB storage and Azure Data Lake Storage.
  Click Check Object Store Access to check if you have access to the object store. You will view a Policy Check wizard with the following bucket lists:

  • OCI list buckets
  • AWS list buckets
  • Azure list buckets

  The Object Storage Listing Policy checker evaluates if you have access to the buckets. If yes, the checker box is highlighted in green with a check sign, else the checker box displays the policy highlighted in red with a red cross.

Under Cloud Service Provider for AI: Select any of the following options from the drop-drown field:

• Oracle Cloud Interface (OCI)
• Amazon Web Services (AWS)

Click Check Cloud Service Access.

You will view the following options in the Cloud Services Policy Checker dialog box. The AI cloud policies listed below must be checked against the listed policies and approved by the Cloud Service vendors for support. The Data Studio tool will test these services and inform you if the data you load in the tool is able to access the services.

• Language- Checks if the Data Studio tool has accessed the Cloud’s language processing abilities. See Use OCI Language Service Capabilities in Data Studio for more information on this service.
• Document Understanding- Checks if the data you load into the Data Studio tool has accessed the Cloud’s Document Understanding AI ability. See Use OCI Document Understanding to extract Tables from Images for more information on this service.
• Translation- Checks if the Data Studio tool accesses the OCI Translation feature. See Perform Text Translation for more information on this service.

On the AI Profile tab of the Data Studio Settings wizard, you can configure your AI preferences.

1. Select AI Profile from the drop-down use this AI profile to support and configure how natural language prompts are translated into SQL statements. The drop-down lists the AI Profiles you create from the Create AI Profile icon. Click + to create AI profile.
   • To utilize the AI services in Data Studio, you must have either an OCI AI or OpenAI or Cohere or Azure OpenAI service account.
   • You must also have access to DBMS_CLOUD_AI package to set your AI profile.
   • If you have Select AI set up using either OpenAI or Cohere or Azure OpenAI service, you can enhance your data by loading small reference data tables that are generated by large language models. Try out the suggested prompts or come up with your own to generate data to load into the autonomous database.

     You can also use this AI profile to generate Marketplace dataset description and tags. This AI profile is used to generate table description in Catalog App.

     See Use DBMS_CLOUD_AI to Configure AI Profiles to create and configure your AI profile.

2. Click Check AI Access.

   The AI Policy checker checks for the following service:

   • Generative AI- The Data Studio tool checks if it has access to the Generative AI service.
3. Under Manage AI Profiles, you can view a tabular data that displays information about the AI Profile. It displays the following field values based on the AI Profile:
   • Profile Name
   • Provider
   • Credential
   • Model
   • Actions: You can edit any of the fields you configured to create the AI Profile. You can also delete the AI profile.

   For more details on the column fields displayed under Manage AI Profiles, refer to Create AI Profile.

On the Vector Index tab of the Data Studio Settings wizard, you can create Vector Index.

Note:

You cannot view the Vector Index tab with Oracle AI Database 19c.

You can view a list of Vector Indexes under Manage Vector Indexes. If you do not have an available Vector Index, click Create Vector Index.

Selecting Create Vector Index, opens Create Vector Index wizard.

1. On the Required Settings tab, you can view the fields that configure the vector index you create and specify the source from which its data is loaded:
   • Vector Index Name: Specify the name of the vector index object that you create using this wizard. You can use this name in SQL and in the console to manage or query the index.​
   • Location: Select a cloud location of the source data for indexing from the drop-down field. You can also type the location name. It is an Object Storage bucket or similar cloud store that the database reads from when building or refreshing the vector index.​
   • AI Profile: Select the AI profile you create from the AI Profile tab in the Data Studio Settings wizard. This field uses the Vector Index linked to the AI profile field in the Create AI Profile wizard.
   • Object Storage Credential Name: Select a stored credential from the drop-down that allows the database to securely access the specified Object Storage location (for example, an OCI user credential or resource principal-based credential).​

   You can click Create to create the Vector Index and skip the Optional Field values.

   Click Next to specify the following Optional field values.

   These optional fields control how documents are chunked, indexed, and retrieved during vector search. You can optionally fill these fields to control how the vector index is built, updated, and queried so that it returns useful results for your workload.

2. On the Optional Settings, specify the following field values:
   • Chunk Size: Specify the number of characters (or tokens, depending on implementation) in each piece of text that is embedded and stored as one vector. Larger chunks capture more context but may be less precise for passage-level matches.​
   • Chunk Overlap: Specify the amount of overlap between consecutive chunks so that content near boundaries appears in multiple chunks, reducing the chance of missing relevant text that falls at a split point.​
   • Refresh Rate: Specify the Interval (in minutes) at which the vector index is automatically refreshed from the source data so that new or updated content is re-embedded and searchable.
   • Vector Distance Metric: Specifies the similarity metric used to compare vectors when searching (for example, COSINE), which determines how “closeness” between query and stored vectors is computed.
   • Match Limit: Specifies the maximum number of results the vector search returns for each query.
   • Similarity Threshold: Specifies the minimum similarity score a result must have to be returned from a vector search. Results with scores below this threshold are filtered out as not relevant enough.​​​

   Click Create to create Vector Index.

   After creating the Vector Index, you can Edit a previously created AI Profile from Manage AI Profiles and add the Vector Index.

On the SMTP tab of the Data Studio Preferences wizard, you can configure email service like a local email client on your system (e.g., Thunderbird).

Note:

You must configure SMTP only once and then the system uses the saved configuration from that point forward.

Specify the following field values in the SMTP tab of the wizard:

1. Server host: Enter the endpoint used to send the email. For example, internal-mailrouter.oracle.com.
2. Server port: Enter the SMTP port used to accept an email. Email Delivery supports TLS on port 25. Sender:
3. Enter the email address of the sender. For example, [e-mail].
4. Server Encryption: This field indicates if TLS, the standard means of performing encryption in transit for emails, is being used. Providers must encrypt emails while it's in transit to the Oracle Cloud Infrastructure Email Delivery service. Encrypted emails are protected from being read during transit. If there is no encryption, enter, None.

5. Select credential to use for SMTP connection from the drop-down. If there is no available credential in the drop-down, you can create credential by clicking Create Credential icon. Refer to Create Oracle Cloud Infrastructure Native Credentials for more details.

Click Test to test the SMTP configuration. You will view a screen that asks you to run the ACL script. You can run the script if you have the ADMIN rights. This is just a first time setting. After you receive a successful message of SMTP Test, you can save the SMTP configuration.

On the Marketplace tab, you can set the configurations you require for the Data Marketplace tool.

Access to data in Data Marketplace is restricted based on user authorizations. As non admin users you have permission to access the Data Marketplace tool based on the Data Studio Settings configuration. You can view the following options:

• Restricted, Requires Authorization:

  Selecting this option enables you to publish restricted cloud links and, consequently, restricted marketplace listings. You will have the ability to grant and revoke access to these listings to specific OCIDs.

• Publish:

  This option specifies who and from where you are allowed to access the registered table.

  You can choose from any of the following available options:

  • TENANCY: You can grant remote data access to any resource, tenancy, compartment, or database in the tenancy of the Autonomous Database instance that is registering the data set. This scope is more restrictive than the REGION scope.
  • COMPARTMENT: You can grant remote data access to any resource, compartment, or database in the compartment of the Autonomous Database instance that is registering the data set.
  • REGION: You can grant remote data access via cloud links to other tenancies in the Autonomous Database instance that is registering the data set.

    Note:

    Marketplace listing currently can only be published up to the compartment level. The tool does not allow you to publish a marketplace listing to entire region for security reasons.
  • None: You do not have access to any resource.
• Read:

  This option allows READ access for the specific user to access the registered table.

On the Slack tab you can configure your Slack profile to receive notifications on certain events while using the Jobs feature.

Specify the following field values:

• Slack Credential Name: Enter the Credentials from the drop-down. The drop-down lists the credentials in your compartment. Click + to create your own credentials.
  • Selecting + opens a Create Credential dialog box. Specify the following field values to create a credential:
    • Credential Name: Enter a name of your choice. For example, SLACK_CRED.
    • Cloud Service: Select Slack from the drop-down.
    • Username: Enter your OCI user name. You must use Oracle Cloud Infrastructure User Name from your profile in the OCI console. For example: oracleidentitycloudservice/[e-mail]. or

      default/[e-mail]

    • Password: *********. For the slack provider, the username value can be any valid string and the password is the Slack bot token.

      Click Create Credential to create a new credential.

    Enter this value in the Slack Credential Name field.

• Slack Channel ID: This specifies the Channel ID in a String value. The Channel ID is a unique ID for a channel and is different from the channel name. In Slack, when you view channel details you can find the Channel ID on the About tab.

• Slack Message: Enter a message to test the notifications.

  Click Test to test the notification. You receive a confirmation message after you successfully authenticate into Slack from Data Studio Settings.. Click Save to set the Slack Credential.

  You can refer to the Create Job to set up notifications to receive Slack alerts about the status of a job run.

On the Share provider Identity tab you can provide the details of the provider before you share the data. The share provider identification will be available to recipients with whom you grant the share while using the Data Share tool. This provides information to the recipient on how to identify you.

Specify the following field values:

• Name: Enter the name of the provider. For example, ams.
• Email: Enter the email address of the provider. For example, [e-mail].
• Description: Enter a description of the provider. For example, AMS sharing stuff.

Click Save to save the provider identification information. You will receive a successful message of configuring the provider identification information.

Select Apply Changes to save and apply the configuration you made in the Marketplace tab of the Data Settings dialog.

You have successfully set and configured your preferences in the Data Studio Settings wizard.

• Slack Integration with Data Studio
  You can integrate Data Studio with Slack on Data Studio Settings using Slack Channel ID and Credentials. With this configuration you can send or schedule reports of the Jobs feature when certain events occur in Slack. The team members of the Slack channel can view the updates, discuss the data insights, and make well informed decisions.
• Create AI Profile
  Autonomous AI Database uses AI profiles to facilitate and configure access to an LLM and to setup for generating, running, and explaining SQL based on natural language prompts using Data Studio.