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Data Sources

A data source in Adaptive Integration specifies the location of the specific spreadsheet or database from which to extract information, user ID and password information, configuration information for which columns or tables to use, and other information that Adaptive Integration needs to access the data you want.


Adaptive Integration can import data from many places. Because you may wish to extract different kinds of data from the same or different spreadsheet or database, you can set up multiple data sources to meet your needs. For example, you might have one data source that imports data for sales orders, a second that imports data for sales expenses, and a third that imports data for sales revenue received, all from the same or from different spreadsheets or databases, depending on which table/column gets chosen.

You can set up a variety of data sources:

  • Spreadsheets You can extract information from Excel spreadsheets. Each worksheet in the spreadsheet is treated as a separate table. See Setting up a Spreadsheet Data Source.

  • Relational databases (RDBMS) You can extract information from any database that is JDBC-compliant. (Note: When you are extracting information from a JDBC-compliant database, you must use a data agent, an application you set up behind your firewall with the Adaptive Data Agent Service Manager, that helps Adaptive Integration communicate with the database You must have at least one agent on any computer that extracts information from a JDBC-compliant database.) See Setting up a JDBC Database Data Source.

  • NetSuite You can use the NetSuite adapter to import data from a NetSuite account. See Setting up a NetSuite Data Source.

  • Intacct You can use the Intacct adapter to import data from an Intacct accountSee Setting up an Intacct Data Source.

  • Microsoft Dynamics GP You can use a Microsoft Dynamics GP adapter to import data from a Microsoft Dynamics GP account. See Setting up a Microsoft Dynamics GP Data Source.

  • Table groups You can create a data source that extracts information from existing staging tables present in different data sources. The underlying data sources can themselves be based on different spreadsheets and databases. This type of data source is helpful in creating joins of tables across different data sources. See Setting Up a Table Group.

  • Salesforce You can use a Salesforce adapter to import data from a Salesforce account. See Setting up a Salesforce Data Source.

  • Scripted data sources You can write Kettle ETL instructions to specify information sources to extract data from and then apply customer-specific business rules to the extracted data. Scripted data sources let you solve complex, custom data extraction and transformation scenarios. Scripted data sources are for advanced ETL implementers who have experience writing Pentaho Kettle scripts and using the Spoon UI. For more information about Pentaho Kettle and Spoon, including extensive documentation and tutorials, please see the Pentaho wiki at See Setting up a Scripted Data Source.

    WARNING: There is no automatic upgrade or migration of the platform or the scripts used within Kettle. If you intend to use the legacy data agent (with Kettle 4.4), you must use the link in the Download Legacy Agent section in the Agent UI of Adaptive Integration. If you have an older Pentaho Kettle version (4.4) and would like to change to Kettle 6, you will need to reinstall the new Data Agent and the new Kettle version on a system that has never had any version of Kettle installed previously.

  • Custom Cloud Data Source (CCDS) You can create custom data sources, authored in JavaScript, to connect to internet addressable systems and supply data to Adaptive products. Custom Cloud Data Sources let you access data from Yahoo Finance, Google Docs, Uber, Weather Underground, or any other site that allows pulling data via JavaScript. Only an Integration user with the Integration Developer permission may enter the JavaScript required to build a CCDS. (Note: For more on creating a CCDS, see our CCDS Developer Guide).

As part of the data source, you can create new columns derived from extracted data, use SQL filters and SQL table joins to filter and select the data you import, and change the data type of extracted data.

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