How to Work with Sage 300 Data in ETL Validator JDBC

ETL Validator provides data movement and transformation capabilities for integrating data platforms across your organization. CData's JDBC driver seamlessly integrates with ETL Validator and extends its native connectivity to include Sage 300 data.

This tutorial explains how to build a simple ETL validator data flow to extract data from Sage 300 data and load it into an example data storage solution: SQL Server.

Add a new ETL Validator data source via CData

CData extends ETL Validator's data connectivity capabilities by providing the ability to add data sources that connect via CData's JDBC drivers. Connecting to Sage 300 data simply requires creating a new data source in ETL Validator through CData's connectiviy suite as described below.

Login to ETL Validator

Begin by logging into ETL Validator to view the application dashboard.

👁 Access the ETL Validator dashboard

Click on Add a DataSource

CData extends the data source options within ETL Validator.

👁 Create a new DataSource

Click on CData

CData's connectivity is embedded within ETL Validator's data source options.

👁 CData data source

Configure the CData Driver Connection String

You will need a JDBC connection string to establish a connection to Sage 300 in ETL Validator.

👁 CData data source

Sage 300 requires some initial setup in order to communicate over the Sage 300 Web API.

• Set up the security groups for the Sage 300 user. Give the Sage 300 user access to the option under Security Groups (per each module required).
• Edit both web.config files in the /Online/Web and /Online/WebApi folders; change the key AllowWebApiAccessForAdmin to true. Restart the webAPI app-pool for the settings to take.
• Once the user access is configured, click https://server/Sage300WebApi/ to ensure access to the web API.

Authenticate to Sage 300 using Basic authentication.

Connect Using Basic Authentication

You must provide values for the following properties to successfully authenticate to Sage 300. Note that the provider reuses the session opened by Sage 300 using cookies. This means that your credentials are used only on the first request to open the session. After that, cookies returned from Sage 300 are used for authentication.

• Url: Set this to the url of the server hosting Sage 300. Construct a URL for the Sage 300 Web API as follows: {protocol}://{host-application-path}/v{version}/{tenant}/ For example, http://localhost/Sage300WebApi/v1.0/-/.
• User: Set this to the username of your account.
• Password: Set this to the password of your account.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Sage 300 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.sage300.jar

👁 Using the built-in connection string designer to generate a JDBC URL (sage 300 is shown.)

A typical connection string looks like this:

jdbc:sage300:User=SAMPLE;Password=password;URL=http://127.0.0.1/Sage300WebApi/v1/-/;Company=SAMINC;

Licensing the Driver

To ensure the JDBC driver is licensed appropriately, copy the license file to the appropriate location:

Copy the JDBC Driver for Sage 300 and lic file from "C:\Program Files\CData[product_name]\lib" to "C:\Datagaps\ETLValidator\Server\apache-tomcat\bin".

 cdata.jdbc.sage300.jar
 cdata.jdbc.sage300.lic
 

Note: If you do not copy the .lic file with the jar, you will see a licensing error that indicates you do not have a valid license installed. This is true for both the trial and full versions.

Save the connection

Should you encounter any difficulties loading the CData JDBC driver class, please contact DataGap's team, and they will provide you instructions on how to load the jar file for the relevant driver.

Add SQL Server as a Target

This example will use SQL Server as a destination for Sage 300 data data, but any preferred destination can be used instead.

Go to DataSources and select MS_SQL_SERVER

This option is the default.

👁 Add SQL Server

Fill in the necessary connection details and test the connection

The details will depend on the specific target, but these details may include a URL, authentiation credentials, etc.

👁 Add SQL Server

Create a Dataflow in ETL Validator

Open the Dataflows tab

Configured data flows will appear in this window.

👁 Dataflows tab

Select Create Dataflow

Name your new dataflow and save it.

Open the Dataflow to view the Dataflow Diagram

The details of the data movement will be configured in this panel.

👁 Dataflow diagram

Drag & drop the JDBC as a source from the right side

Give the new source an appropriate name and save it.

👁 Jira example source

Fill in the Query section of the new source

Select the Table from the Schema option that reflects which data should be pulled from Sage 300 data.

View the expected results of your query

The anticipated outcome of the configured query is displayed in the Result tab.

👁 Query results

Add the destination to the Dataflow

Select Switch to Diagram, then drag & drop the DB Sink as a target from the right side (under Sink options). Give the sink an appropriate name and save it.

👁 Data sink

Set the appropriate Schema for the destination

Choose the Schema and table that matches the structure of the source table. For this example, the table on the target side was created to match the Source so that data flow seamlessly. More advanced schema transformation operations are beyond the scope of this article.

👁 Destination schema

Hit the RUN option to begin replication

Running the job will take some time.

👁 Destination schema

View the finished Dataflow

Return to the diagram to see the finished data replication job from Sage 300 data to SQL Server.

👁 Full dataflow

Get Started Today

Download a free, 30-day trial of the CData JDBC Driver for Sage 300 and start building Sage 300-connected applications with ETL Validator. Reach out to our Support Team if you have any questions.