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Access Microsoft Dataverse data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for Microsoft Dataverse and the RJDBC package to work with remote Microsoft Dataverse data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Microsoft Dataverse and visualize Microsoft Dataverse data by calling standard R functions.
CData provides the easiest way to access and integrate live data from Microsoft Dataverse (formerly the Common Data Service). Customers use CData connectivity to:
CData customers use our Dataverse connectivity solutions for a variety of reasons, whether they're looking to replicate their data into a data warehouse (alongside other data sources)or analyze live Dataverse data from their preferred data tools inside the Microsoft ecosystem (Power BI, Excel, etc.) or with external tools (Tableau, Looker, etc.).
You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.
To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:
library(RJDBC)
You will need the following information to connect to Microsoft Dataverse as a JDBC data source:
The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for Microsoft Dataverse:
driver <- JDBC(driverClass = "cdata.jdbc.cds.CDSDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.cds.jar", identifier.quote = "'")
You can now use DBI functions to connect to Microsoft Dataverse and execute SQL queries. Initialize the JDBC connection with the dbConnect function.
You can connect without setting any connection properties for your user credentials. Below are the minimum connection properties required to connect.
When you connect the Common Data Service OAuth endpoint opens in your default browser. Log in and grant permissions. The OAuth process completes automatically.
For assistance in constructing the JDBC URL, use the connection string designer built into the Microsoft Dataverse JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.cds.jar
Fill in the connection properties and copy the connection string to the clipboard.
👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)Below is a sample dbConnect call, including a typical JDBC connection string:
conn <- dbConnect(driver,"jdbc:cds:OrganizationUrl=https://myaccount.crm.dynamics.com/;InitiateOAuth=GETANDREFRESH;")
The driver models Microsoft Dataverse APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:
dbListTables(conn)
You can use the dbGetQuery function to execute any SQL query supported by the Microsoft Dataverse API:
accounts <- dbGetQuery(conn,"SELECT AccountId, Name FROM Accounts WHERE Name = 'MyAccount'")
You can view the results in a data viewer window with the following command:
View(accounts)
You can now analyze Microsoft Dataverse data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:
par(las=2,ps=10,mar=c(5,15,4,2)) barplot(accounts$Name, main="Microsoft Dataverse Accounts", names.arg = accounts$AccountId, horiz=TRUE)👁 A basic bar plot. (Salesforce is shown.)
Download a free trial of the Microsoft Dataverse Driver to get started:
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