Known methods and techniques to help create better results with university data.
Things to consider first
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Make sure to follow the same rules
University data is more than just spreadsheets and presentations - it’s information gathered about students, academics, budgets, human resources, research, and facilities.
Each of these domains have their own stewards and policies following institutional or legal standards. This is also known as data governance.
Make sure to consider any risks
Each new tool that connects to university data also needs to be secure, which means it's possible that it will need to be reviewed by Cybersecurity to see what risk might be involved.
Each tool poses a potential security risk and may need to go through a Risk Management Framework with the campus cybersecurity team.
All tools will need to be secure and not expose campus to any unintended issues. Whether you discover a new tool, or select a pre-approved everyday data tool, there is help available to strategize and identify any red flags or concerns.
Make sure to think of the big picture
In order to be good stewards of university resources, it's good practice to see if there is an existing solution first. It can save time and money.
Once a tool has been approved, there is still planning needed to ensure its continued success. Conversations should also take place about:
- Training
- Maintenance
- Who will support the new tool
Make sure it's accessible to everyone
If you are considering adding a new product or tool, digital accessibility should be part of the decision making process.
Buying accessible technology | Evaluating technology for accessibility
Where to begin
Just getting started? Try this:
Tips on how to best approach your question that may involve data and information technology including:
Common questions, rules and policies, security, accessibility, working with a third-party tool or vendor, and who to talk to for assistance.
Best practices when it comes to compliance
Facilitating campus-wide data-driven decision making that’s aligned with UW-Madison priorities.
Intake analyses, security assessments, risk management, and security control implementation.
Policy, procedures, data access, management and use standards when it comes to institutional data.
Best practices in using data tools
In addition to the things to consider first, each tool often at used at UW-Madison may have its own documentation and training materials. There are also communities of practice to crowdsource an answer.
Everyday data tools
There are many tools used to access, and analyze to gain insights. These are some of the most common ones used at UW-Madison.
- Badger Analytics
- InfoAccess
- Lumen
- Student Information System (SIS)
- Tableau
- RADAR, Repository of Administrative Dashboards and Reports
- UW Business Intelligence (UWBI, OBIEE, OAS)
- WISPER, Wisconsin Proposal Electronic Routing
- WISER: formerly known as WISDM (or Wisconsin Data Mart)
- SAS
- Microsoft Excel
- Microsoft Access
- Oracle SQL Developer
Data integration tools
These many involve using custom applications or integration code to allow systems to exchange data, seek to deploy or enhance IT systems to support and streamline business processes.
- Informatica Intelligent Cloud Services (data integrations)
- API Developer Portal (Apigee)
- Manifest (Automate access privileges as a person’s role changes. Manage groups of users to provision and de-provision access.)
Service principles
Ready to launch into a data integration? Want to understand the best ways to make sure your work benefits UW-Madison as a whole?
12 Interoperability Service Principles
Principles to help us create and run great interoperability services at UW-Madison. They were developed in collaboration with campus partners and include best practices.
Get help
General questions
Talk to an expert to get answers, guidance, and advice for your specific question.
Data Stewards
The point person to help get access to the institutional data you need to use.
Crowdsourced
Folks who frequently use, access, and share data at UW-Madison.
TechPartners, Data Wonks, BI Community of Practice, more tech support groups