Everyday data tools and training

Where to get started when you use everyday data tools or commonly available data sets to gain deeper insights or support your decision making.

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

Change is coming

Process improvements

The Office of Data Management and Analytics Services (ODMAS) is working to modernize and expand the capabilities of UW–Madison’s enterprise data warehouse, as part of a larger project called "Badger Analytics."

Badger Analytics will soon replace InfoAccess

Use cases

Getting access to institutional data

Searching for where data exists

Querying institutional data sources

Reporting results to inform decisions

Analyzing and interpreting data

 Creating data visualizations

Types of data

The most common types of institutional data available at UW-Madison. Sometimes these are also called types of “data views.”

Academic, or Student Administration


Human Resources



Everyday data tools

Tools used on a daily basis at UW-Madison for a variety of needs including reporting, analyzing, and gaining insights.

InfoAccess/Badger Analytics and Snowflake | Student Information System (SIS) | Tableau | Lumen | RADAR | UW Business Intelligence UWBI | Oracle Business Intelligence OBIEE | Oracle Analytics Server OAS | WISPER | WISER | Excel | SAS | Access | Oracle SQL Developer


InfoAccess, Badger Analytics, and Snowflake

UW-Madison’s data warehouse containing academic, budget, human resources, research, and facility data from sources including:

  • Student Information System (SIS)
  • Budget System
  • Shared Financial System (SFS)
  • Person Hub, Human Resource System (HRS)

*Badger Analytics is the new campus new cloud analytics environment that uses the platform Snowflake, and will eventually replace InfoAccess.

Get access | Using InfoAccess | Help documents | Email list


A data visualization tool that allows users to interact with institutional data through dynamic and interactive dashboards, maps, and other presentation formats.

  • Some are public reports, some have restricted access
  • Publishing to Tableau requires approval

Get access | Using Tableau | Help documents | Training: LinkedIn LearningMadison Tableau User Group

Lumen (Academic and curricular management tools)

A centralized location to update, track, and approve functions related to UW-Madison courses, curriculum and programs. Lumen is available through MyUW.

Get access | Using Lumen

RADAR, Repository of Administrative Dashboards and Reports

  • Including academic, curricular, faculty & staff, finance, research, and student data

Get access | Using RADAR

UW Business Intelligence (UWBI, OBIEE, OAS)

A UW System focused analytics platform including administrative and institution-specific systems such as human resources, student data, and financials.

*UW Oracle Business Intelligence Enterprise Edition (OBIEE) tool has been upgraded to Oracle Analytics Server (OAS).

Get access | Using UW Business Intelligence | Help documents | Training

WISPER, Wisconsin Proposal Electronic Routing

UW-Madison system for electronic routing of applications and agreements related to extramural funding.

Get access | Using WISPER | Help documents | Training

WISER: formerly known as WISDM (or Wisconsin Data Mart)

UW-Madison’s financial accounting system

  • A part of Shared Financial Systems (SFS), also a web-based financial reporting system used by all UW system campuses.
  • Detail and summary financial reports by department, sub-department, division and projects.
  • View reports on line, in PDF or down load to Excel.
  • Demographic data on projects/grants.
  • Transaction searches of payments, transfers, internal billings, purchase orders and other journals.

Get access | Login | TrainingUsing WISER

SAS (Statistical Analysis System)

Statistical analysis and data visualization for reporting and analytics

  • Connect to a variety of data sources and build queries
  • Replaces Toad Data Point

Get access | Training and support

Microsoft Excel

A spreadsheet tool used for analysis of data, and for generating insights. A university supported tool available for use through the Campus Software Library.

Get access | Training: LinkedIn Learning | Help documents

Microsoft Access

A database management system used to integrate data sources, create databases, and find data with queries. A university supported tool available for use through the Campus Software Library.

Get access | Training: LinkedIn Learning, Microsoft

Oracle SQL Developer

A database management system for running queries and scripts against an Oracle database, extracting data, reporting, and data modeling.

Get access | Training: LinkedIn Learning, Oracle University