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University of California Riverside Case Study - Higher Education

Modernized Data Extraction and Analysis for University

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The summary.

The University of California Riverside is a Top 100 US research university with 25,000+ students and 1,100+ faculty. We built a modernized data extraction and analysis platform to inform student-success priorities, delivering data marts, dashboards, and data-quality testing on BigQuery, Looker, and dbt.

University of California Riverside
2.5years
Engagement length
Main technologies used
Python
BigQuery
SQL
Engagement model

About University of California Riverside

The University of California Riverside features in the Top 100 best Universities in the US. They have 25,000+ students and 1,100+ faculty members.

The challenge.

The University of California Riverside wanted to build a data model to help inform student-success strategic priorities. They needed to build datasets and fact tables through an improved data extraction process, and to build dashboards that could segment and analyze students by demographics, cohorts, and degree info, with the goal of decreasing dropout rates.

We have a 14-year track record of delivering expert tech solutions for 500+ clients across dozens of industries.

UCR decided to partner with us.

UCR wanted to build a data model to inform student-success priorities, needing improved data extraction, fact tables, and dashboards that segment students by demographics, cohorts, and degree info to decrease dropout rates.

The solution.

UCR chose our software outsourcing engagement model. We provided 7 nearshore software engineers with Python, BigQuery, SQL, Looker, dbt, and Google Cloud Storage expertise to modernize their data pipeline, build dashboards, and establish a data-quality testing layer.

All technologies used.

Python
BigQuery
TestRail
SQL
Looker
DBT
Google Cloud
The outcome

The outcome.

At the end of the initial 5-month project, we:

  • Delivered 4 data marts to retrieve relevant raw data and populated 4 fact tables with this information.
  • Built 4 dashboards for data analysis and visualization.
  • Performed +800 data quality tests including data freshness, data volume, schema change, and anomalies tests.
  • Integrated data with Looker and dbt, providing better data analytics capabilities.
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