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Data Integration

The Data Integration team facilitates the design and construction of scalable and robust data pipelines that efficiently process and integrate data at scale from various systems within campus and external vendors into the Enterprise Data Lakehouse. Our goal is to provide efficient, reliable, and comprehensive datasets for downstream systems, stakeholders, analytics teams, and business operations.

What We Enable

  • Data Pipeline Design and Development: Design and develop comprehensive data pipelines to facilitate the following key activities involving Data Collection, Data Enrichment, Data Curation, Data access, and Data delivery. 
  • Data Pipeline Architecture & Flow Design: Enable and Enhance the architecture and orchestration of Lakehouse pipelines, ensuring efficient, modular and scalable data flows.
  • Pipeline Performance Optimization: Enhance pipeline speed, reliability, and efficiency through performance tuning and scalability improvements.
  • Data Quality & Governance Collaboration: Embed quality checks and governance standards in pipelines through close partnership with relevant teams.
  • Monitoring & Operational Support: Monitor production health, troubleshoot issues, and ensure timely & consistent data availability.
  • Documentation & Best Practices: Maintain standards, technical documentation, and datasets availability to support consistent development and accessing Data Lakehouse content.

How We Do It

We leverage the data platform, constructed upon a scalable and modular Data Lakehouse architecture. This platform facilitates the comprehensive lifecycle of data integration, transformation, and access. It handles diverse data sources, processes data efficiently, and delivers trusted data for various analytical and operational needs.

Data Platform Components

  • Data Sources: We integrate data from a wide range of systems including:
    • External Systems
    • Cloud-based Applications 
    • On-Premises Applications 
    • Databases 
  • Data Lakehouse Zones: Central to our architecture is the Data Lakehouse, organized into three logical zones:
    • Landing Zone: Raw data is ingested here via secured file transfers, APIs, database integrations, and streaming services.
    • Enriched Zone: This is where raw data is validated, structured, and loaded into staging tables, making it ready for downstream transformation.
    • Curated Zone: Data is transformed, standardized, and blended to produce clean, business-ready datasets optimized for analysis and sharing.
  • Data Access:
    We provide multiple access methods tailored to end-user needs:
    • BI Tools for self-service and ad hoc reporting
    • Data Sharing platforms for controlled distribution
    • APIs for real-time and programmatic access
    • POC & Data Science environments for advanced exploration and modeling

  • Data Delivery:

    We provide secure delivery of curated data to Internal Campus Systems and External Vendors

  • Catalog & Governance:
    Throughout the pipeline, we ensure data is cataloged, discoverable, and governed using metadata management, access controls, and data quality monitoring.

For any further discussions or partnership opportunities for Data Integration, please contact Rajesh Narayanan (rnarayanan@ucla.edu)