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Azure DevOps Icon Azure DevOps ODBC Driver

The Azure DevOps ODBC Driver is a powerful tool that allows you to connect with live data from Azure DevOps, directly from any applications that support ODBC connectivity.

Access Azure DevOps data like you would a database - read, write, and update Azure DevOps Accounts, Approvals, Builds, Tests, etc. through a standard ODBC Driver interface.

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Analyze Azure DevOps Data in R


Create data visualizations and use high-performance statistical functions to analyze Azure DevOps data in Microsoft R Open.

Access Azure DevOps data with pure R script and standard SQL. You can use the CData ODBC Driver for Azure DevOps and the RODBC package to work with remote Azure DevOps 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 Azure DevOps data and visualize Azure DevOps data in R.

Install R

You can complement the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open (MRO).

Connect to Azure DevOps as an ODBC Data Source

Information for connecting to Azure DevOps follows, along with different instructions for configuring a DSN in Windows and Linux environments.

You can connect to your Azure DevOps account by providing the Organization and PersonalAccessToken.

Obtaining a Personal Access Token

A PersonalAccessToken is necessary for account authentication.

To generate one, log in to your Azure DevOps Organization account and navigate to Profile -> Personal Access Tokens -> New Token. The generated token will be displayed.

If you wish to authenticate to Azure DevOps using OAuth refer to the online Help documentation for an authentication guide.

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

Windows

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

Linux

If you are installing the CData ODBC Driver for Azure DevOps in a Linux environment, the driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties.

/etc/odbc.ini

[CData AzureDevOps Source] Driver = CData ODBC Driver for Azure DevOps Description = My Description AuthScheme = Basic Organization = MyAzureDevOpsOrganization ProjectId = MyProjectId PersonalAccessToken = MyPAT

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

Load the RODBC Package

To use the driver, download the RODBC package. In RStudio, click Tools -> Install Packages and enter RODBC in the Packages box.

After installing the RODBC package, the following line loads the package:

library(RODBC)

Note: This article uses RODBC version 1.3-12. Using Microsoft R Open, you can test with the same version, using the checkpoint capabilities of Microsoft's MRAN repository. The checkpoint command enables you to install packages from a snapshot of the CRAN repository, hosted on the MRAN repository. The snapshot taken Jan. 1, 2016 contains version 1.3-12.

library(checkpoint) checkpoint("2016-01-01")

Connect to Azure DevOps Data as an ODBC Data Source

You can connect to a DSN in R with the following line:

conn <- odbcConnect("CData AzureDevOps Source")

Schema Discovery

The driver models Azure DevOps APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

sqlTables(conn)

Execute SQL Queries

Use the sqlQuery function to execute any SQL query supported by the Azure DevOps API.

builds <- sqlQuery(conn, "SELECT Id, BuildNumber FROM Builds WHERE Reason = 'Manual'", believeNRows=FALSE, rows_at_time=1)

You can view the results in a data viewer window with the following command:

View(builds)

Plot Azure DevOps Data

You can now analyze Azure DevOps 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(builds$BuildNumber, main="Azure DevOps Builds", names.arg = builds$Id, horiz=TRUE)