Data Engineering Services

Data Engineering implements modern cloud data architecture for sustainable design and solutioning to meet growing data needs across the Stanford community. We partner with you to:

Develop and manage a data lake/lake house to facilitate efficient storage, analysis, and utilization of diverse data sets
Consolidate and structure data into a standardized format
Implement pipelines to ingest data from various cloud and on-prem data source end points
Create a unified representation of data that aligns more closely with business needs and facilitates improved decision-making and operational efficiency

What we offer

To support data needs at Stanford, the Data Engineering team may implement and support data solutions, including:

Data lake
Data integrations
Data sharing with units
Data science solutions involving artificial intelligence/machine learning (AI/ML)
Data analytics
API development and implementation
Data query and retrieval

Designed for

Groups seeking:

Scalable, reliable data storage for academic research and operational initiatives
Streamlined and optimized data integration, transformation, and analysis workflows for their projects
Data-driven insights to enhance decision-making and achieve institutional goals
Secure, centralized and user-friendly platforms for storing and sharing data across departments
AI and machine learning capabilities to address complex challenges and drive innovation

Data Inventory

Student Data Lakehouse: serving IR&DS and Registrar's office
Athletics Data Lakehouse: serving DAPER department
Analytics Data Lake: for AI Playground and LBRE Occupancy
JIRA Data Lake: for FMS Analytics
RER Program:
- EPM Budget Management data: for BI reporting
- HCM Data Lake: for all Units/Schools. (Going live in July 2026)
ServiceNow Data Lakehouse: for the units/departments analytics and reporting (Going live in April 2026)
CCC Project - Datalake, API and Search: for new Bulletin website for Registrar's office (Going live in Sept. 2026)

Rates

Free of charge