teamUpHR is pleased to announce a set of brand-new Excel for Workday® tools, collectively known as teamUpHR Data Merge(TM).
In my first blog post, I laid out the business case for using Excel to manipulate Workday® data. In this blog post, I’m pleased to demonstrate the culmination of several months’ worth of work, which has brought forth this new set of tools.
Anyone who has used Workday® reporting is aware that it’s possible to pull in multiple related Business Objects to match up related data. But what if you have two data sets that can be matched up based on a common ID, but isn’t available to join in Workday®? What do you do? Well, historically, this would require hours of manual data manipulation in Excel. With our new tool, that all goes away.
teamUpHR Data Merge handles two different use cases: one to many (1:M) and many to one (M:1). If you’ve ever taken a database class, you’d recognize these as expressions of relationship cardinality between two data sets. A 1:M relationship is where one thing is related to many other things. For example, one manager may have many employees. A M:1 relationship is where many things are related to one thing. For example, many employees have the same manager. This might sound like we’re talking about one thing two different ways, and that’s true, but the nuance is that 1:M reports and M:1 reports answer different questions.
In this example a 1:M report answers the question, “Given a manager, who are all the employees that report to him/her?” In contrast, M:1 answers the question, “Given many employees, who are their managers?” Do you see the difference? In the first example, given one row of data, we’re returning multiple rows and columns of additional data. In the second example, given many rows of data, we’re returning the same number of rows of data, but it has additional columns of data appended to it.
Here’s a real example of a one to many (1:M) relationship:
Given the manager, Steve Morgan:
And a list of employees preceded by their manager’s ID:
Give me all the people who report to Steve Morgan:
With Data Merge, the data is merged at the click of a button!
Here’s another real example. This time of a many to one (M:1) relationship:
Given the employee, Oliver Reynolds and some additional columns of data on him:
And a list of Managers with some additional columns of data on them:
Give me the information on Oliver and whoever his manager is:
These might not seem like a very complex, time-consuming operation, but imagine if you had to do either of these examples with a list of 10,000 employees and 10,000 managers. That’s a lot of copying and pasting!
So that is the new teamUpHR Data Merge product. We can’t wait to see what you merge with it, and we look forward to saving you (the Workday® ecosystem) hundreds and thousands of hours of manual merging.