Qlik > Case Studies > Empowering Students Using Qlik AutoML at Weber State University

Empowering Students Using Qlik AutoML at Weber State University

Customer Company Size

Large Corporate

Region

America

Country

United States

Product

Qlik AutoML

Tech Stack

Data warehouse
Analytics Dashboards
Argos
Survey tools
Retention tool

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Productivity Improvements
Customer Satisfaction

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Education

Applicable Functions

Business Operation

Use Cases

Predictive Quality Analytics
Predictive Replenishment

Services

Data Science Services

About The Customer

Weber State University is a state-funded community college as well as a bachelor’s-, master’s-, and — as of recently — doctoral-granting institution in Utah. They are non-selective in which applicants can attend, attracting students from varied educational backgrounds including many developmental students that need additional help in math or English composition. The university has a mission to close the skills gap for these types of students, and they have seen big gains over the last three years.

The Challenge

Weber State University (WSU) began using Qlik AutoML in late Q1 2020, right as the pandemic took hold in the US. As Covid-19 wreaked havoc, the university had difficult decisions to make about where to allot resources in the midst of self-described “survival mode.” A combination of the right power at the right price made Qlik AutoML a viable choice even in uncertain times as a method to empower, support, and retain their students in a quickly-changing world. After a trial month with Qlik AutoML, decision-makers saw value thanks to Qlik AutoML’s ability to translate something complicated to something understandable, making it easier to share with stakeholders with and without technology backgrounds. With limited funding, Qlik AutoML was a more attractive option because of its affordability compared to competitors and consultants that can incur “astronomical expenses,” according to WSU’s Heather Chapman, Director, Academic Analytics.

The Solution

WSU is using Qlik AutoML to fuel a variety of predictive analytics projects and to answer questions including: Persistence - Which students will persist (i.e. come back for the next term)? What are the characteristics of these students? Persistence is a key factor in getting funding for the university. Graduation - Which students were most likely to graduate? What impacted graduating students? Among their most impactful projects so far, WSU discovered that worry-free aid—aid that students did not have to pay back— dramatically impacted a student’s chances of graduating. Graduation is another key factor in determining funding. Accreditation - WSU incorporated predictive analytics into the accreditation process to help quantify and show that the degrees they issue are valuable and meaningful. WSU has many upcoming projects they want to try using Qlik AutoML. The ease and speed of Qlik AutoML is opening more room for idea exploration than previous methods of predictive analytics that required time-consuming, iterative processes.

Operational Impact

Improved understanding and ability to affect graduation and persistence rates, which are critical to schools such as WSU.
The ease and speed of Qlik AutoML is opening more room for idea exploration than previous methods of predictive analytics that required time-consuming, iterative processes.