You’re committed to improving educational outcomes. Don’t let managing student data impede your success.
Longitudinal studies are hard enough to conduct without having to worry about the IT aspects of data management. To build reliable statistical models, above all you need clean and consistent data. But your data providers don’t always send you clean data. Format issues are common, and even if the data formats are correct, the data aren’t always consistent.
(Was that student really a hundred years old, or did the file just list the wrong century for the date of birth?)
Your study may involve data from multiple sources, in which case you’ll need to track students across those sources, from secondary to college, and perhaps even to the workplace. This can be a difficult IT problem, because you can’t rely on any unique student identifier across multiple data providers.
You’ll also need reports in various formats: raw data dumps for your modeling tools, interactive Web reports, and perhaps formatted printable reports in PDF. Excel can only take you so far in reporting. When you have millions of records to manage, you’ll need specialized reporting tools, and those require specialized knowledge.
Then, overhanging all of these concerns are Family Educational Rights and Privacy Act (FERPA) standards for rigorously protecting personally identifiable information.
Considering all that, you might find yourself wanting a little help—and that’s where we come in.
CC Pace has deep experience in data intake, data warehousing, student matching, and reporting. We’ll take care of the difficult IT problems, while you focus on improving educational outcomes. Our accomplishments in custom software for the educational research market include:
- Data intake systems that can process millions of records a minute, with both syntax and semantic validation, and can perform data cleanup driven by customizable rules that identify common input data errors
- Designing and tuning student data warehouses that contain a billion facts and dozens of dimensions, including combinations of relational and unstructured data systems
- Student matching engines whose matching logic can be changed without requiring any IT resources and can match a thousand students per minute
- Extensive knowledge of several reporting engines, both commercial and open source
- Knowledge of the implications of FERPA on the design and implementation of computing and network infrastructure, databases, and Web systems
If success is the only option in your research study, CC Pace is your only choice. Contact us to find out why.