ETL Microsoft Dataverse in Oracle Data Integrator

Leverage existing skills by using the JDBC standard to read and write to Microsoft Dataverse: Through drop-in integration into ETL tools like Oracle Data Integrator (ODI), the CData JDBC Driver for Microsoft Dataverse connects real-time Microsoft Dataverse data to your data warehouse, business intelligence, and Big Data technologies.

JDBC connectivity enables you to work with Microsoft Dataverse just as you would any other database in ODI. As with an RDBMS, you can use the driver to connect directly to the Microsoft Dataverse APIs in real time instead of working with flat files.

This article covers a JDBC-based ETL -- Microsoft Dataverse to Oracle. After reverse engineering a data model of Microsoft Dataverse entities, you will create a mapping and select a data loading strategy -- since the driver supports SQL-92, this last step can easily be accomplished by selecting the built-in SQL to SQL Loading Knowledge Module.

Getting Started

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Install the Driver

To install the driver, copy the driver JAR (cdata.jdbc.cds.jar) and .lic file (cdata.jdbc.cds.lic), located in the installation folder, into the ODI appropriate directory:

• UNIX/Linux without Agent: ~/.odi/oracledi/userlib
• UNIX/Linux with Agent: ~/.odi/oracledi/userlib and $ODI_HOME/odi/agent/lib
• Windows without Agent: %APPDATA%\Roaming\odi\oracledi\userlib
• Windows with Agent: %APPDATA%\odi\oracledi\userlib and %APPDATA%\odi\agent\lib

Restart ODI to complete the installation.

Reverse Engineer a Model

Reverse engineering the model retrieves metadata about the driver's relational view of Microsoft Dataverse data. After reverse engineering, you can query real-time Microsoft Dataverse data and create mappings based on Microsoft Dataverse tables.

1. In ODI, connect to your repository and click New -> Model and Topology Objects. 👁 Create a New Model
   
2. On the Model screen of the resulting dialog, enter the following information:
   • Name: Enter CDS.
   • Technology: Select Generic SQL (for ODI Version 12.2+, select Microsoft SQL Server).
   • Logical Schema: Enter CDS.
   • Context: Select Global.
   👁 Configuring the Model
   
3. On the Data Server screen of the resulting dialog, enter the following information:
   • Name: Enter CDS.
   • Driver List: Select Oracle JDBC Driver.
   • Driver: Enter cdata.jdbc.cds.CDSDriver
   • URL: Enter the JDBC URL containing the connection string.

     You can connect without setting any connection properties for your user credentials. Below are the minimum connection properties required to connect.

     • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
     • OrganizationUrl: Set this to the organization URL you are connecting to, such as https://myorganization.crm.dynamics.com.
     • Tenant (optional): Set this if you wish to authenticate to a different tenant than your default. This is required to work with an organization not on your default Tenant.

     When you connect the Common Data Service OAuth endpoint opens in your default browser. Log in and grant permissions. The OAuth process completes automatically.

     Built-in Connection String Designer

     For assistance in constructing the JDBC URL, use the connection string designer built into the Microsoft Dataverse JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

     java -jar cdata.jdbc.cds.jar
     

     Fill in the connection properties and copy the connection string to the clipboard.

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     

     Below is a typical connection string:

     jdbc:cds:OrganizationUrl=https://myaccount.crm.dynamics.com/;InitiateOAuth=GETANDREFRESH;
     

   👁 Configuring the Data Server
   
4. On the Physical Schema screen, enter the following information:
   • Name: Select from the Drop Down menu.
   • Database (Catalog): Enter CData.
   • Owner (Schema): If you select a Schema for Microsoft Dataverse, enter the Schema selected, otherwise enter CDS.
   • Database (Work Catalog): Enter CData.
   • Owner (Work Schema): If you select a Schema for Microsoft Dataverse, enter the Schema selected, otherwise enter CDS.
   👁 Configuring the Physical Schema
   
5. In the opened model click Reverse Engineer to retrieve the metadata for Microsoft Dataverse tables. 👁 Reverse Engineer the Model
   

Edit and Save Microsoft Dataverse Data

After reverse engineering you can now work with Microsoft Dataverse data in ODI. To edit and save Microsoft Dataverse data, expand the Models accordion in the Designer navigator, right-click a table, and click Data. Click Refresh to pick up any changes to the data. Click Save Changes when you are finished making changes. 👁 Viewing the data.

Create an ETL Project

Follow the steps below to create an ETL from Microsoft Dataverse. You will load Accounts entities into the sample data warehouse included in the ODI Getting Started VM.

1. Open SQL Developer and connect to your Oracle database. Right-click the node for your database in the Connections pane and click new SQL Worksheet.

   Alternatively you can use SQLPlus. From a command prompt enter the following:

   sqlplus / as sysdba
   

2. Enter the following query to create a new target table in the sample data warehouse, which is in the ODI_DEMO schema. The following query defines a few columns that match the Accounts table in Microsoft Dataverse:

   CREATE TABLE ODI_DEMO.TRG_ACCOUNTS (NAME NUMBER(20,0),AccountId VARCHAR2(255));
   

3. In ODI expand the Models accordion in the Designer navigator and double-click the Sales Administration node in the ODI_DEMO folder. The model is opened in the Model Editor.
4. Click Reverse Engineer. The TRG_ACCOUNTS table is added to the model.
5. Right-click the Mappings node in your project and click New Mapping. Enter a name for the mapping and clear the Create Empty Dataset option. The Mapping Editor is displayed.
6. Drag the TRG_ACCOUNTS table from the Sales Administration model onto the mapping.
7. Drag the Accounts table from the Microsoft Dataverse model onto the mapping.
8. Click the source connector point and drag to the target connector point. The Attribute Matching dialog is displayed. For this example, use the default options. The target expressions are then displayed in the properties for the target columns.
9. Open the Physical tab of the Mapping Editor and click ACCOUNTS_AP in TARGET_GROUP.
10. In the ACCOUNTS_AP properties, select LKM SQL to SQL (Built-In) on the Loading Knowledge Module tab. 👁 SQL-based access to Microsoft Dataverse enables you to use standard database-to-database knowledge modules.
    

You can then run the mapping to load Microsoft Dataverse data into Oracle.