Migrating data from Workday to Google BigQuery using CData SSIS Components.



Easily push Workday data to Google BigQuery using the CData SSIS Tasks for Workday and Google BigQuery.

Google BigQuery is a serverless, highly scalable, and cost-effective data warehouse designed to help organizations turn big data into actionable insights.

The CData SSIS Components enhance SQL Server Integration Services by enabling users to easily import and export data from various sources and destinations.

In this article, we explore the data type mapping considerations when exporting to BigQuery and walk through how to migrate Workday data to Google BigQuery using the CData SSIS Components for Workday and BigQuery.

Data Type Mapping

Google BigQuery Schema CData Schema

STRING, GEOGRAPHY, JSON, INTERVAL

string

BYTES

binary

INTEGER

long

FLOAT

double

NUMERIC, BIGNUMERIC

decimal

BOOLEAN

bool

DATE

date

TIME

time

DATETIME, TIMESTAMP

datetime

STRUCT

See below

ARRAY

See below


STRUCT and ARRAY Types

Google BigQuery supports two kinds of types for storing compound values in a single row, STRUCT and ARRAY. In some places within Google BigQuery, these are also known as RECORD and REPEATED types.

A STRUCT is a fixed-size group of values that are accessed by name and can have different types. The component flattens structs so their fields can be accessed using dotted names. Note that these dotted names must be quoted.

An ARRAY is a group of values with the same type that can have any size. The component treats the array as a single compound value and reports it as a JSON aggregate. These types may be combined such that a STRUCT type contains an ARRAY field, or an ARRAY field is a list of STRUCT values.

Special Considerations

  • Google BigQuery has both DATETIME (no timezone) and TIMESTAMP (with timezone) data types that the CData SSIS Components map to datetime based on the timezone of your local machine.
  • In Google BigQuery, the NUMERIC type supports 38 digits of precision and up to 9 digits after the decimal point, while the BIGNUMERIC type supports 76 digits of precision and up to 38 digits after the decimal point. The CData SSIS Components for Google BigQuery automatically detects the precision/scale, but with the Destination Component users can manually map any high-precision columns.
  • INTERVAL data types:
    • The component represents INTERVAL types as strings. Whenever a query requires an INTERVAL type, it must specify the INTERVAL using the BigQuery SQL INTERVAL format:
      YEAR-MONTH DAY HOUR:MINUTE:SECOND.FRACTION
    • For example, the value "5 years and 11 months, minus 10 days and 3 hours and 2.5 seconds" in the correct format is:
      5-11 -10 -3:0:0.2.5

About Workday Data Integration

CData provides the easiest way to access and integrate live data from Workday. Customers use CData connectivity to:

  • Access the tables and datasets you create in Prism Analytics Data Catalog, working with the native Workday data hub without compromising the fidelity of your Workday system.
  • Access Workday Reports-as-a-Service to surface data from departmental datasets not available from Prism and datasets larger than Prism allows.
  • Access base data objects with WQL, REST, or SOAP, getting more granular, detailed access but with the potential need for Workday admins or IT to help craft queries.

Users frequently integrate Workday with analytics tools such as Tableau, Power BI, and Excel, and leverage our tools to replicate Workday data to databases or data warehouses. Access is secured at the user level, based on the authenticated user's identity and role.

For more information on configuring Workday to work with CData, refer to our Knowledge Base articles: Comprehensive Workday Connectivity through Workday WQL and Reports-as-a-Service & Workday + CData: Connection & Integration Best Practices.


Getting Started


Prerequisites

Create the project and add components

  1. Open Visual Studio and create a new Integration Services Project.
  2. Add a new Data Flow Task to the Control Flow screen and open the Data Flow Task.
  3. Add a CData Workday Source control and a CData GoogleBigQuery Destination control to the data flow task.

Configure the Workday source

Follow the steps below to specify properties required to connect to Workday.

  1. Double-click the CData Workday Source to open the source component editor and add a new connection.
  2. In the CData Workday Connection Manager, configure the connection properties, then test and save the connection.

    To connect to Workday, users need to find the Tenant and BaseURL and then select their API type.

    Obtaining the BaseURL and Tenant

    To obtain the BaseURL and Tenant properties, log into Workday and search for "View API Clients." On this screen, you'll find the Workday REST API Endpoint, a URL that includes both the BaseURL and Tenant.

    The format of the REST API Endpoint is: https://domain.com/subdirectories/mycompany, where:

    • https://domain.com/subdirectories/ is the BaseURL.
    • mycompany (the portion of the url after the very last slash) is the Tenant.
    For example, in the REST API endpoint https://wd3-impl-services1.workday.com/ccx/api/v1/mycompany, the BaseURL is https://wd3-impl-services1.workday.com and the Tenant is mycompany.

    Using ConnectionType to Select the API

    The value you use for the ConnectionType property determines which Workday API you use. See our Community Article for more information on Workday connectivity options and best practices.

    APIConnectionType Value
    WQLWQL
    Reports as a ServiceReports
    RESTREST
    SOAPSOAP

    Authentication

    Your method of authentication depends on which API you are using.

    • WQL, Reports as a Service, REST: Use OAuth authentication.
    • SOAP: Use Basic or OAuth authentication.

    See the Help documentation for more information on configuring OAuth with Workday.

  3. After saving the connection, select "Table or view" and select the table or view to export into Google BigQuery, then close the CData Workday Source Editor.

Configure the Google BigQuery destination

With the Workday Source configured, we can configure the Google BigQuery connection and map the columns.

  1. Double-click the CData Google BigQuery Destination to open the destination component editor and add a new connection.
  2. In the CData GoogleBigQuery Connection Manager, configure the connection properties, then test and save the connection.
    • Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app. OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, register an application to obtain the OAuth JWT values. In addition to the OAuth values, specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

    Helpful connection properties

    • QueryPassthrough: When this is set to True, queries are passed through directly to Google BigQuery.
    • ConvertDateTimetoGMT: When this is set to True, the components will convert date-time values to GMT, instead of the local time of the machine.
    • FlattenObjects: By default the component reports each field in a STRUCT column as its own column while the STRUCT column itself is hidden. When this is set to False, the top-level STRUCT is not expanded and is left as its own column. The value of this column is reported as a JSON aggregate.
    • SupportCaseSensitiveTables: When this property is set to true, tables with the same name but different casing will be renamed so they are all reported in the metadata. By default, the provider treats table names as case-insensitive, so if multiple tables have the same name but different casing, only one will be reported in the metadata.
  3. After saving the connection, select a table in the Use a Table menu and in the Action menu, select Insert.
  4. On the Column Mappings tab, configure the mappings from the input columns to the destination columns.

Run the project

You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.

Ready to get started?

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