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Steps To Higher Education Data Cleanliness: A Technical Perspective
Introduction As data is collected daily through the heavy use of computers and the internet, we continue to be plagued by the problem of dirty data. Data that is error prone or inconsistent leads to bad outcomes, such as misguided decision making...
How to Pull Data From the Cloud: Things to Consider in Higher Education
More and more applications (software) are residing in the cloud. In the past, these applications were often viewed as black boxes. This means the end user sees an interface but has little insight into the processing that goes on within them. But...
IPEDS Surveys: What Does the Process Cost?
So far, we’ve taken a look at the top mistakes made during IPEDS submission and some steps you can take to reduce bad data entry during that process. But once that process is done, that’s it. Right? You’ve crossed the finish line. You’ve slain the...
IPEDS Data Entry: How to Reduce Basic Data Errors
Question: How many times have you, when reviewing IPEDS data, found basic data entry errors? Better question: How many times have you missed such errors prior to submission? The issues around data entry errors in IPEDS surveys are very real and...
Top IPEDS Submission Mistakes: Based on Real Conversations
The IPEDS submission process is typically not a smooth one. From accessing to collecting to validating to formatting IPEDS data, there are numerous stages where mistakes can – and often do – occur. We’ve assembled a list of some of the most common...
IPEDS Surveys Reporting: ‘Tis the Season (Part 2)
“Duck Season! Rabbit Season! IPEDS Season!” While duck seasons and rabbit seasons come and go, it always seems to be IPEDS season. So, we’re here to continue our examination of the IPEDS survey process. In part 1 we looked at the various challenges...
IPEDS Surveys Reporting: ‘Tis the Season (Part 1)
“To everything there is a season.” Whether you recognize that line from The Bible or The Byrds, it’s a commonly known phrase with wide-ranging applications. For Institutional Researchers, the everything is their IPEDS surveys and the season is...
Improving Accessibility for Argos Dashboards
When designing a dashboard, you're usually thinking about things like which parameters are required, the type of information your users want to see, and how you can lay everything out on the form so that it makes sense. What you might not have...
Using Maturity Models for Data Validation in Higher Education
There are multiple ways of assessing where your institution is at regarding data validation and data governance. In this discussion, we’ll look at data validation as it relates to maturity models. The maturity model is an assessment of the data...
How to Build Trust In Your Higher Education Data: 10 Key Steps
Higher education institutions need to trust their data so that they can engage in effective decision-making. But building trust is not easy. So, we figured we would provide you our ten steps to build this trust. 1. Data requests should be a...
Higher Education Data Governance Explained
If you work at a college or university, there may be plenty of topics that generate more attention than “data governance,” but do any of these three ‘progress-stoppers’ ring a bell? You’re in the Office of Institutional Research. Today, your job...
Best Practices for Dashboard Design
The difference between an art museum and an art gallery is subtle. Museums showcase art for the art enthusiast – for interest, critique or discussion. Museums tend to be grandiose, containing all types of art, separated by theme or artist. While...
Best Practices for Charting Your Higher Education Institution’s Data
“One Picture is Worth a Thousand Words.” The phrase, often attributed to Fred Barnard after it appeared in the advertising trade journal Printer’s Ink, also applies to the visual presentation of data. While our focus is often on higher education,...
Overcoming Data Integration Issues
Data. It’s a simple word. Yet collecting it, analyzing it, and understanding it isn’t always so simple. For institutions of higher education, this is usually the result of two circumstances: 1) Data from one source does not always match data from...
The 5 Most Commonly Found Metrics for Student Success
There is much debate on how to define and measure student success. At first glance, it seems simple: a successful student is a first-year who enrolls in college full-time, persists through terms, and then progresses to degree completion. However,...