Dana-Farber Cuts Time for Data Access and Transformation Using Monarch

Tom Pellerin at Dana-Farber Cancer Institute has been using Monarch for 15-16 years.

As a reimbursement manager, he handles monthly net-revenue calculations that require combining disparate reports for analysis.

Monarch allows him to extract and blend data from text reports, PDF reports, and databases to analyze variances from revenue on a monthly basis.

My name’s Tom Pellerin and I work at Dana Farber. I’ve been using Monarch probably for about 15 to 16 years. I’m a reimbursement manager so I do monthly net revenue calculations that we use various reports for and use Monarch to help expedite and analyze the data that we’re using. It allows us to take data from PDF reports that we might need to extract some of the information from and then analyze that data. We extract it and put it into Excel using Monarch. It also allows us to access various databases and pull that information into Monarch and filter things down to let us analyze various pairs. And, also we pull in text reports to get GL data. We use that to look at variances from revenue and expenses on a monthly basis. Also we use Monarch for our various ad hoc analysis to basically help us gather the information that we need and filter things down. You spend a lot of time adjusting, eliminating page headers if you have to parse things in Excel. You’d have to parse out all the page headers, this eliminates that. You’d have probably a lot of mistakes from data that you’re not capturing or wrong numbers that you wouldn’t be capturing. If you build summaries in the model it allows you to calculate back that the data you extracted matches the reports. At Datawatch Monarch it definitely is a huge time saver and it is a tremendous analytical tool, and I would recommend it to anybody. Buy Datawatch Monarch.

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