August 16, 2010 - Financial Business Service Centers, Kuali Financial System at Cornell
The following is a post from the Kuali Financial System at Cornell Blog.
In my last blog post, I discussed the work of the KFS Interfaces team. This time around, I’d like to highlight the critical work of the Data Conversion team. If you look at the data in the KFS Test Drive, which is what the system is delivered with out of the box, you’ll see it is a combination of sample data and Indiana University reference data. This may be useful when first trying to understand the basics of the system; however, it won’t meet the full needs of the KFS Implementation project, and it definitely won’t meet the long-term operational needs of Cornell. In order to do that, we need to fulfill the request we’ve heard many times from the KFS module teams: “We need Cornell data!”
There are many steps in the process of populating the KFS system with Cornell data. First, we need to understand the KFS database, including what data is required, along with information about it such as its size and shape. This process began a few years ago with analysis against the previous KFS version, v2.0. Next, we need to understand where we can get Cornell data that can be loaded into the KFS database, and whether it needs to be transformed in case KFS expects a different format than what exists in our legacy systems. In some cases, we need to load data into KFS that does not exist in legacy data sources, and so we need to work with various functional team members to generate new data.
The next step is to load the data into KFS. After the data is loaded, we need to validate that it is correct. Based on the validation results, we may need to change the data conversion process, transformation rules, or input data. KFS contains a large amount of data, so these steps are repeated iteratively so we can focus on a subset of data at a time.
The Data Conversion team has been working with the Chart of Accounts team to make sure the new chart of accounts is populated correctly in KFS. This work has been ongoing since early on in Phase 1 of the implementation. Recently, the Data Conversion team has been focused in two new areas: loading account balance data in preparation for rolling out the pre-production instance of KFS, and loading parameter (configuration) and maintenance value (reference) data to help the module teams better understand and utilize KFS with Cornell data.
The Data Conversion team will also be working with each module team to ensure that the data they need, beyond parameters and maintenance values, is loaded into the system. A lot of excellent work has been done by the Data Conversion team to date, with more significant work to come. It’s all toward helping meet the goal of a fully implemented KFS system with Cornell data.
Development Manager, Kuali Financial System Implementation