Data Project Requirements
This article will outline the requirements and guidelines for having the software engineering team complete a data project for you or your department. If you have single or multiple data sets in spreadsheets or applications and you would like to do any of the following this article is for you:
- Improve data storage/design practices
- Increase efficiency or automate data movement
- Create reports/aggregate single or multiple data sets
- Integrate multiple data sources in a single system
- Aquire access to use frequently updated student-athlete roster or staff data in your data sets
Project Life Cycle
We are more than happy to work with you to help increase efficiency/automate your data needs, but you should be aware of the following:
- Data projects generally take at a minimum of 2 weeks if it is a singular spreadsheet/source. They can take 3+ months if it is a large project with API integrations and multiple data sets.
- Requesters should expect to meet with the software engineering team on a recurring basis until project completion. That includes the following development steps:
- Gathering Analysis
- Design
- Integration
- Implementation
- Testing
- Steps may go through multiple iterations as design may change based on testing
- You or some part of your staff may have some additional responsibilities as part of the end product
- Example:
- You may need to manually run a job or do a data export/import
- You may need to keep track of bugs/errors to report to our team
- Example:
Data Classification Standards
If your data contains sensitive data above a Low (Level 1) classification (see here for reference) and will live in a 3rd party application we must have the Division of IT security team review the vendor's data infrastructure.
Requesting a Data Project Consultation Session
You can request a data project consultation by submitting request on athleticsit.umd.edu
Please complete the following tasks before reaching out for a consultation
- Prepare your data sets with a clear list of data points
- Prepare what insights and questions you would like answered if we are reporting on data
- If applicable, reach out to the vendor for a technical point of contact