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Author Power BI Reports on Real-Time Sage 300 Data

Use the CData Power BI Connector for Sage 300 to visualize Sage 300 data in Power BI.

CData Power BI Connectors provide self-service integration with Microsoft Power BI. The CData Power BI Connector for Sage 300 links your Power BI reports to real-time Sage 300 data. You can monitor Sage 300 data through dashboards and ensure that your analysis reflects Sage 300 data in real time by scheduling refreshes or refreshing on demand. This article details how to use the Power BI Connector to create real-time visualizations of Sage 300 data in Microsoft Power BI Desktop.

If you are interested in publishing reports on Sage 300 data to PowerBI.com, refer to our other Knowledge Base article.

Collaborative Query Processing

The CData Power BI Connectors offer unmatched performance for interacting with live Sage 300 data in Power BI due to optimized data processing built into the connector. When you issue complex SQL queries from Power BI to Sage 300, the connector pushes supported SQL operations, like filters and aggregations, directly to Sage 300 and utilizes the embedded SQL Engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze Sage 300 data using native Power BI data types.

Connect to Sage 300 as a Power BI Data Source

Installing the Power BI Connector creates a DSN (data source name) called CData Power BI Sage 300. This the name of the DSN that Power BI uses to request a connection to the data source. Configure the DSN by filling in the required connection properties.

You can use the Microsoft ODBC Data Source Administrator to create and configure the DSN: From the Start menu, enter "ODBC Data Sources" and select the CData PowerBI REST DSN. Ensure that you run the version of the ODBC Administrator that corresponds to the bitness of your Power BI Desktop installation (32-bit or 64-bit). You can also use run the ConfigureODBC.exe tool located in the installation folder for the connector.

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.

Query Sage 300 Tables

Follow the steps below to build a query to pull Sage 300 data into the report:

  1. Open Power BI Desktop and click Get Data -> Other -> CData Sage300.
  2. Select CData PowerBI Sage 300 in the Data Source Name menu and select a data connectivity mode:
    Select Import if you want to import a copy of the data into your project. You can refresh this data on demand.
    Select DirectQuery if you want to work with the remote data.
  3. Select tables in the Navigator dialog.
  4. In the Query Editor, you can customize your dataset by filtering, sorting, and summarizing Sage 300 columns. Click Edit to open the query editor. Right-click a row to filter the rows. Right-click a column header to perform actions like the following:

    • Change column data types
    • Remove a column
    • Group by columns

    Power BI detects each column's data type from the Sage 300 metadata retrieved by the connector.

    Power BI records your modifications to the query in the Applied Steps section, adjusting the underlying data retrieval query that is executed to the remote Sage 300 data. When you click Close and Apply, Power BI executes the data retrieval query.

    Otherwise, click Load to pull the data into Power BI.

Create Data Visualizations

After pulling the data into Power BI, you can create data visualizations in the Report view by dragging fields from the Fields pane onto the canvas. Follow the steps below to create a pie chart:

  1. Select the pie chart icon in the Visualizations pane.
  2. Select a dimension in the Fields pane: for example, InvoiceUniquifier.
  3. Select a measure in the Fields pane: for example, ApprovedLimit.

You can change sort options by clicking the ellipsis (...) button for the chart. Options to select the sort column and change the sort order are displayed.

You can use both highlighting and filtering to focus on data. Filtering removes unfocused data from visualizations; highlighting dims unfocused data. You can highlight fields by clicking them:

You can apply filters at the page level, at the report level, or to a single visualization by dragging fields onto the Filters pane. To filter on the field's value, select one of the values that are displayed in the Filters pane.

Click Refresh to synchronize your report with any changes to the data.

At this point, you will have a Power BI report built on top of live Sage 300 data. Learn more about the CData Power BI Connectors for Sage 300 and download a free trial from the Sage 300 Power BI Connector page. Let our Support Team know if you have any questions.