The Analytics and Data Solutions department provides four main types of services:
Data Management
Data Management services provide faculty and staff with access to reporting data and to specialists to review data cleanliness and quality. The latest industry tools are used to help standardize and normalize enterprise data across the university. This service enables data integrity for research and reporting.
Confidential Data Profiling
Data profiling looks at similarities with the data as a percentage of the total. It includes a review of data type, duplication, null values, and more.
This service helps to helps identify sensitive data such as social security numbers. The discovery of sensitive data requires that it be reported to the department and MSU Information Security. A plan to address sensitive data is created jointly.
Data Quality Reviews
Data quality reviews are an in-depth assessment that include a component for cleansing the data. Data quality and the same format for similar fields is important to ensure accuracy. For example, MI, Mich, and Michigan could all be listed in state field.
Recommendations on how to scrub the data are provided after the review.
Data Warehousing
The MSU Enterprise Data Warehouse (MSUEDW) is comprised of the university’s central data repositories. Analysts can help set up ways the MSUEDW can be directly accessed, queried, and analyzed to fit your business needs.
Human Resource, Finance, Organizational, Student, Research Administration, and other university data are housed in this secured environment.
Access to the MSUEDW
A request for access to the data must be completed and approved.
- For student data: Complete the Student Access Request Memorandum form (MSUEDW-SIS ARM PDF).
- For Kuali Coeus Research Administration data: Complete the Research Administration Access Request Memorandum form (MSUEDW-KCRA ARM PDF).
- For other data in the MSUEDW: Complete the standard Access Request Memorandum form (MSUEDW ARM PDF).
Add data to the MSUEDW
Colleges and units can add application data to the warehouse. Several benefits can be realized:
- helps insulate the application from other applications written against that data
- any additional application can reference the data warehouse instead of the source application
- reduces the load and overhead of an interface
- frees the source application to make necessary changes
- only need to update the data warehouse feed
- links to other applications from the data warehouse are not broken by the source application change
Data Analytics
The Data Analytics service provides faculty and staff access to licensed university staff and software to create standard reports and visualization for common business or college information. There are also predictive tools for decision makers.
Reporting
Standard enterprise reports can answer common business questions (e.g., Labor Distribution, Operation Statement, Account Balance Summary). Consultation is also available to assist in building self-service reports that answer specific college or department questions.
Visualization
Data visualizations such as dashboards can be personalized to provide a quick snapshot of important information. Charts, graphs, and other visual elements that summarize and answer common business questions are also available.
Predictive Analytics
Analytics and Data Solutions can apply mathematical and statistical algorithms to interpret, make inferences, and draw conclusions about internal and external data sets. This set of activities enables decision makers to review options to maximize a desired outcome.
An example is the Student Success Dashboard, which uses past data and predictive analytics to establish success markers for each major, unit, and college. These markers come from an analysis of data that identify student performance patterns influencing persistence and graduation. Advisors are trained to use the Student Success Dashboard tool, as well as on ethical use of data and interviewing techniques to support MSU students.
