Analyze Talkdesk Data in R via JDBC

Access Talkdesk 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 Talkdesk and the RJDBC package to work with remote Talkdesk 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 Talkdesk and visualize Talkdesk data by calling standard R functions.

Install R

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.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to Talkdesk as a JDBC Data Source

You will need the following information to connect to Talkdesk as a JDBC data source:

• Driver Class: Set this to cdata.jdbc.talkdesk.TalkdeskDriver
• Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

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 Talkdesk:

driver <- JDBC(driverClass = "cdata.jdbc.talkdesk.TalkdeskDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.talkdesk.jar", identifier.quote = "'") 

You can now use DBI functions to connect to Talkdesk and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

Talkdesk uses the OAuth 2.0 Client Credentials grant. There is no browser-based authorization step and no callback URL.

Set the following connection properties:

• AccountName: The name of your Talkdesk account.
• Region: The region where your Talkdesk instance is deployed. Supported values are US (default), EU, CA, AU, UK, and FedRamp.
• OAuthClientId: The Client Id assigned when you registered your custom OAuth application.
• OAuthClientSecret: The Client Secret assigned to your custom OAuth application.

Creating a Custom OAuth Application

1. Log in to your Talkdesk account and select OAuth Clients from the navigation menu.
2. Click Create OAuth Client and give the client a descriptive name.
3. Set Grant Type to Client Credentials.
4. Click Add scopes and select the scopes for the data you want to access.
5. Click Create and copy the Client Id and Client Secret.

When you connect, the driver automatically requests an access token from Talkdesk, caches it, and refreshes it when it expires. Make sure the scopes selected for the application match the views you plan to query, or the token request can fail.

Built-in Connection String Designer

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

java -jar cdata.jdbc.talkdesk.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:talkdesk:AccountName=myAccount;Region=US;OAuthClientId=myClientId;OAuthClientSecret=myClientSecret;")

Schema Discovery

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

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the Talkdesk API:

users <- dbGetQuery(conn,"SELECT Id, Name FROM Users WHERE Active = 'true'")

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

View(users)

Plot Talkdesk Data

You can now analyze Talkdesk 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(users$Name, main="Talkdesk Users", names.arg = users$Id, horiz=TRUE)