Data Analytics is the process of reviewing expenditure data on federal awards for identification of high risk transactions. Expenditure data (referred to as the General Ledger or GL) from the UW’s financial system is downloaded into a spreadsheet and the data is then organized and analyzed to identify high risk or questionable transactions.
The UW’s Data Analytics Program downloads and analyzes the expenditure data from the GL then provides it to campus for their review. At the School/College level, it may also provide an opportunity to review trends or anomalies. The transaction identified are those that we anticipate could be questioned in the event of an audit or other sponsor review.
Campus is encouraged to review the data and graphs to identify trends, gaps in internal controls, training opportunities, and any other areas of concern. Individual transaction data is provided to assist in this review.
The reports are made available to the School/College administrators. For department specific reports, contact the Dean’s office or send a request for access to PAFC (firstname.lastname@example.org).
Information on each of the Data Analytics Reports is provided by topic below.
- Cost/Expense Transfers Data Analytics Report- Cost Transfers (CTs) are considered to be high risk as they can be an indication of weak Internal Controls. For more general information on Cost Transfers and links to Elearning course and other training opportunities visit the Cost Transfers page.
- End-of-Award Equipment Purchase Report- The End-of-Award Equipment report provides a list of all Equipment purchases with indicators for those purchases near or after the Award end date. As all purchases must benefit an Award, Equipment purchased at the end of an Award is high risk as it can be either difficult to prove how the Equipment benefitted the Award in a limited amount of time or an indicator of weak Internal Controls as it can be perceived that the purchase was made to utilize a balance of Award funding.