For supported source applications such as NetSuite and Salesforce, Celigo sync includes native awareness of your data structure and functionality to assist you in configuring the table-level data to prepare it for extraction. In Step 1: Source of creating a sync, after choosing the application and connection, you’ll see an Objects or NetSuite saved searches tab before the ubiquitous Exports tab when object support is built in.
For any source application, you can build or reuse an export (from Flow builder or a standalone resource) to provide data for a sync source. The way in which you preview, select, and configure table- and field-level data differs between the two source types.
Objects offer the most user-friendly and quick method for choosing your source data. Wherever possible, Celigo sync does the work for you to catalog the application data – and supply additional information about the schema – to extract the objects for ingestion to a database or data warehouse destination.
Each object represents a table that you can simply click to select or further configure.
Exports will give you the greatest flexibility in precisely accessing the source data. However, if your flows and syncs don’t already contain a reusable export suitable for your requirements, you will have to build one or more custom exports before you can start creating a sync.
Tip
For data ingestion exports, look for a List or Get all endpoint in your application’s API guide, or write an inclusive SQL statement. For example, to sync Zendesk tickets, you could configure an export to get all Zendesk tickets, without any additional input parameters. That is, for data ingestion, you almost always want to try to retrieve as much of the context as possible. To extract all of the data from an API endpoint, then choose Export type: All; for incremental data, choose Delta.
Lacking source application metadata for an export, Celigo sync attempts to provide default values for data ingestion:
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The initial table name is derived from the export name. For example, click the export “Get Shopify customers” to modify the placeholder Destination table name value
get_shopify_customers, according to the table where you want it to be ingested. -
Celigo relies on sample requests to infer the data type of each column in the source schema. For example, compare the values in the export Preview (left, below) with the assigned data types for each column (right, below). The key
created_atresolves to a DATETIMENTZ data type,currencyis a STRING with 3 characters, and so on.