Integrate Google Analytics with FintechOS

Google Analytics offers great data about the traffic on a website. It is an all-round tool to see who from where using what device accesses your website. In the following steps, we will explain the integration process with Google Analytics Account with FintechOS Platform using Data Pipes.

1 Configure your Google Analytics OAuth credential type

  1. Access https://console.developers.google.com/apis/credentials.
  2. From credentials menu select Create new credentials.
  3. Select OAuth Client ID.
  4. Application Type select from the drop-down Web Application.
  5. From https://analytics.google.com select the account ID you want to integrate with FintechOS.
  6. Follow the path: FintechOS Studio > Evolutive Data Model > Data Pipes > Connections. Create the Data Pipes Connection with Google Analytics from FintechOS Studio.
  7. For Add Connection select Google Analytics. For Profile, insert the link you previously saved. In Advanced, for OAuth JWT Subject write GETANDREFRESH.
  8. Click the Save and reload button.

    IMPORTANT!  
    You must enable TLS or login from the local machine to authenticate with this site, hence, you will need to make the connection from the server.

2 Create a Data Pipes Job to connect your source and destination

  1. Follow the path: FintechOS Studio > Evolutive Data Model -> Data Pipes -> Jobs.

  2. Click the Add Job button, select source and destination.
  3. From Add tables menu, select the tables you want to import.

  4. From the Advanced menu, untick AlterSchema.

  5. Destination Schema: ebs

  6. Follow the path: FTOS-Studio -> Evolutive Data Mode -> Data Model Explorer. Create your Database Destination Tables and populate them with the same attributes as the source.

  7. The Entity type will be: External Source Data.

  8. The Primary Key Attribute from the Source table needs to be replicated in the destination with Is External Id or the attribute type need to be set as UniqueIdentifier.

  9. From the Data Pipes Jobs, check again if your Data Model matches the table name and structure.

  10. Run the job or configure the scheduler.

For more details, see Data Pipes.