Tackling the Data Quality Challenge
Common data quality challenges higher ed faces—and a sample action plan
Colleges and universities face daunting data quality hurdles.
Data needs across campus are soaring, yet uncollected, inconsistent, and impossible to aggregate data silos are impairing decision-making and ultimately preventing institutions from progressing toward their strategic goals.
Our brief explores the most common data challenges that higher education faces and four key principles to guide data quality initiatives at any institution:
- Identifying who needs to participate in discussions
- Defining key terms consistently
- Standardizing the data quality process
- Establishing processes for sustainable quality
As a complement to the brief, this data self-test will allow you to quickly assess your maturity. Use the test as a conversation piece to help other leaders understand where you are—and where you could be regarding data and analytics capabilities. Take the diagnostic.
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