Although Digital Measures is unable to measure for data quality accuracy, it’s important to have a process in place to regularly monitor and cleanse the records that exist in the system. To begin improving your accuracy, remember that the best way to spot flaws in data accuracy is to have a general reliance on the reports in Digital Measures. The more users there are using reports from the system, the more eyes there are to spot possible inaccuracies.
You can review the attached Data Quality packet or the article, Data Quality: The Basics, for a more thorough explanation of each metric.
To start improving accuracy, it’s important to build a process around updating owned data that comes from a campus source system. This can include data from the following screens.
- Personal and Contact Information
- Yearly Data
- Permanent Data
- Scheduled Teaching
- Academic Advising
- Contracts, Fellowships, Grants and Sponsored Research
Since data on these screens tend to have an authoritative system, it’s important to build a solid CSV upload or web service workflow to automate a consistent stream of accurate records. In addition to updating frequently, develop an open channel of communication for faculty to address any inaccuracies in this owned data. We recommend adding help text on these screens to direct faculty to the correct person who can update the source, which will trickle down to Digital Measures during the next process.
Besides concrete processes of updating data from source system, we recommend creating custom reports with the specific purpose of data cleansing for accuracy. These reports can be tailored based on the metrics your campus finds most important. For example, if collaborating with students on research is a key metric on campus, it might be valuable to build a custom report that specifically displays research records, breaking out collaborators, roles and if a student was involved, in an easy to review table for a quick accuracy analysis.
Your Success Consultant can help you determine the best action items to address your particular issues. A few potential outcomes may be:
- Identifying key metrics that might necessitate a custom data cleansing report.
- Make all key metric fields required to ensure quality data for this metric moving forward.
- Enlist the help of data entry workers on campus to monitor core fields to ensure accurate values.
Improving your accuracy will give you confidence that Digital Measures will produce comprehensive reports that include records correctly and in the correct format because everyone is entering their data in the same manner.