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 and reliable data storage solutions to support academic research or operational initiatives.
- Groups looking to streamline and optimize data integration, transformation, and analysis workflows for their projects.
- Groups focused on leveraging data-driven insights to enhance decision-making and achieve institutional goals.
- Groups interested in accessing secure, centralized, and user-friendly platforms for storing and sharing data across departments.
- Groups exploring AI and machine learning capabilities to address complex challenges and drive innovation.
Rates
Free of charge
