Migrating data from Outlook to Google BigQuery using CData SSIS Components.

Google BigQuery is a serverless, highly scalable, and cost-effective data warehouse designed to help organizations turn big data into actionable insights.

The CData SSIS Components enhance SQL Server Integration Services by enabling users to easily import and export data from various sources and destinations.

In this article, we explore the data type mapping considerations when exporting to BigQuery and walk through how to migrate Outlook data to Google BigQuery using the CData SSIS Components for Outlook and BigQuery.

Data Type Mapping

STRUCT and ARRAY Types

Google BigQuery supports two kinds of types for storing compound values in a single row, STRUCT and ARRAY. In some places within Google BigQuery, these are also known as RECORD and REPEATED types.

A STRUCT is a fixed-size group of values that are accessed by name and can have different types. The component flattens structs so their fields can be accessed using dotted names. Note that these dotted names must be quoted.

An ARRAY is a group of values with the same type that can have any size. The component treats the array as a single compound value and reports it as a JSON aggregate. These types may be combined such that a STRUCT type contains an ARRAY field, or an ARRAY field is a list of STRUCT values.

Special Considerations

• Google BigQuery has both DATETIME (no timezone) and TIMESTAMP (with timezone) data types that the CData SSIS Components map to datetime based on the timezone of your local machine.
• In Google BigQuery, the NUMERIC type supports 38 digits of precision and up to 9 digits after the decimal point, while the BIGNUMERIC type supports 76 digits of precision and up to 38 digits after the decimal point. The CData SSIS Components for Google BigQuery automatically detects the precision/scale, but with the Destination Component users can manually map any high-precision columns.
• INTERVAL data types:
  • The component represents INTERVAL types as strings. Whenever a query requires an INTERVAL type, it must specify the INTERVAL using the BigQuery SQL INTERVAL format:

    YEAR-MONTH DAY HOUR:MINUTE:SECOND.FRACTION

  • For example, the value "5 years and 11 months, minus 10 days and 3 hours and 2.5 seconds" in the correct format is:

    5-11 -10 -3:0:0.2.5

Prerequisites

• Visual Studio 2022
• SQL Server Integration Services Projects extension for Visual Studio 2022
• CData SSIS Components for Google BigQuery
• CData SSIS Components for Outlook

Create the project and add components

1. Open Visual Studio and create a new Integration Services Project.
2. Add a new Data Flow Task to the Control Flow screen and open the Data Flow Task.
3. Add a CData Outlook Source control and a CData GoogleBigQuery Destination control to the data flow task.

Configure the Outlook source

Follow the steps below to specify properties required to connect to Outlook.

1. Double-click the CData Outlook Source to open the source component editor and add a new connection.
2. In the CData Outlook Connection Manager, configure the connection properties, then test and save the connection.

   Using OAuth Authentication

   Microsoft Graph API uses OAuth 2.0 for authentication. You must register an application in the Microsoft Azure Portal to obtain OAuth credentials (Client ID and Client Secret).

   Obtaining OAuth Credentials

   1. Log in to the Azure Portal.
   2. Navigate to Azure Active Directory > App registrations.
   3. Click New registration to create a new application.
   4. Enter an application name and select the appropriate account types.
   5. Set the Redirect URI to your application's callback URL (e.g., http://localhost:33333 for desktop apps).
   6. Click Register to create the application.
   7. On the application overview page, copy the Application (client) ID - this is your OAuthClientId.
   8. Navigate to Certificates & secrets and create a new client secret.
   9. Copy the client secret value - this is your OAuthClientSecret.
   10. Navigate to API permissions and add the required Microsoft Graph API permissions:
       • Mail.Read - For accessing email messages
       • Contacts.Read - For accessing contacts
       • Calendars.Read - For accessing calendar events
       • Tasks.Read - For accessing To Do tasks
       • offline_access - For obtaining refresh tokens
   11. Click Grant admin consent to grant these permissions.

   Connecting with OAuth

   After setting the following connection properties, you are ready to connect:

   • AuthScheme: Set this to OAuth.
   • InitiateOAuth: Set this to GETANDREFRESH. The CData API Profile for Outlook will automatically walk through the OAuth process in order to obtain the access token.
   • OAuthClientId: Set this to the Application (client) ID from Azure Portal.
   • OAuthClientSecret: Set this to the client secret value from Azure Portal.
   • TenantId: Set this to your Azure AD tenant identifier (GUID or domain name like 'contoso.onmicrosoft.com').
   • CallbackURL: Set this to the Redirect URI you specified in your app registration (e.g., http://localhost:33333 for desktop apps).

   Example connection string

   Profile=C:\profiles\Outlook.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;TenantId=your_tenant_id;CallbackUrl=http://localhost:33333;
   

   
3. After saving the connection, select "Table or view" and select the table or view to export into Google BigQuery, then close the CData Outlook Source Editor.

Configure the Google BigQuery destination

With the Outlook Source configured, we can configure the Google BigQuery connection and map the columns.

1. Double-click the CData Google BigQuery Destination to open the destination component editor and add a new connection.
2. In the CData GoogleBigQuery Connection Manager, configure the connection properties, then test and save the connection.
   • Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app. OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, register an application to obtain the OAuth JWT values. In addition to the OAuth values, specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

   Helpful connection properties

   • QueryPassthrough: When this is set to True, queries are passed through directly to Google BigQuery.
   • ConvertDateTimetoGMT: When this is set to True, the components will convert date-time values to GMT, instead of the local time of the machine.
   • FlattenObjects: By default the component reports each field in a STRUCT column as its own column while the STRUCT column itself is hidden. When this is set to False, the top-level STRUCT is not expanded and is left as its own column. The value of this column is reported as a JSON aggregate.
   • SupportCaseSensitiveTables: When this property is set to true, tables with the same name but different casing will be renamed so they are all reported in the metadata. By default, the provider treats table names as case-insensitive, so if multiple tables have the same name but different casing, only one will be reported in the metadata.
   
3. After saving the connection, select a table in the Use a Table menu and in the Action menu, select Insert.
4. On the Column Mappings tab, configure the mappings from the input columns to the destination columns.

Run the project

You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.