Appflow all object for google ads

AWS AppFlow currently allows you to create a flow for a single object or entity at a time. However, there are a few ways you can approach creating a flow for multiple objects or campaigns:

Chained Flows: You can create multiple AppFlow flows, where each flow extracts data from a single object, and then chain these flows together. For example, you could create one flow to extract campaigns, another flow to extract leads, and then use the output of the campaigns flow as the input for the leads flow.

Customized Extraction: Instead of relying on the pre-defined objects in your source system, you can use a custom query or SQL statement to extract the data you need. This way, you can pull data from multiple objects or tables into a single flow.
    For example, if your source system is a relational database, you can use a SQL query to select the campaign data from multiple tables and have AppFlow ingest that combined data.
    If your source is a SaaS application, you may be able to leverage their API to construct a custom query that retrieves the campaign data across multiple objects.

Intermediate Data Storage: You can use an intermediate data storage solution, such as Amazon S3 or Amazon Redshift, to stage the data from multiple objects before ingesting it into your target system. Here's how it would work:
    Create an initial AppFlow flow to extract data from each individual object (e.g., campaigns, leads, etc.) and store the data in an S3 bucket or Redshift table.
    Then, create a second AppFlow flow that reads the data from the intermediate storage and consolidates it into a single, unified dataset before sending it to the target system.

Scheduled Flows: If your use case involves regularly extracting and consolidating data from multiple objects, you can set up a scheduled flow. This way, the flow will automatically run at a specified interval (e.g., daily, weekly) and handle the extraction and consolidation of data from the various objects.

The best approach will depend on the specific requirements of your use case, the structure of your data sources, and the capabilities of the source and target systems involved. I'd recommend exploring these different options and choosing the one that best fits your needs.