Note: Code has been redacted and altered so as to not infringe on privacy

I typically use R, JavaScript and LaTeX in my programmatic endeavours.

This innovation used R+LaTeX which is called “Sweave”

I knew JIRA data flows to DOMO and I knew I could get access to the DOMO backend I sought an access token. After finding the right person and becoming buddies I was granted a unique key.

DomoR:fetch function pulls relevant data set into R Studio so parsing and manipulation can occur.

DomoR::init(‘customer’, ‘token’)

df <- DomoR::fetch(‘unique dataset ID’)

More can be found here: https://github.com/domoinc-r/DomoR

Manipulate the 64,000 rows of data and 400 columns into a usable format.

26 million data points

Subset data by Account Manager, Status, Disqualified or not, program type, etc..

Sweave’s (shown beside) purpose is “to create dynamic reports, which can be updated automatically if data or analysis change”. This in combination with an auto-emailer script provided sales with a personal report email weekly.

Circumventing the needs for licensing while maintaining automatic data flow via an adjacent system.

• Using R & Sweave (LateX for PDF generation) provide a read-out of a personalized sales report.
• Show’s where, when and if capital is approved.
• Show’s performance of each individual sales executive.
• Show’s if contract is signed.
• Show’s in graph format what type of build would be required VS. if capital is approved.
• Show’s Status of funnel for each item assigned to the account executive.

• Provide Leadership with entire program view.
• Subset by Project Manager
• Subset by Partner Company
• Stats-in-year breakdown