Data Engineering
Ingest, structure, and transform heterogeneous data for research-ready use.
Manage structured and unstructured data using a robust set of tools, from ingestion to integration, ensuring traceability, scalability, and readiness for analysis.
Bring your own structured datasets into the high-performance Manifold database. An AI assistant accelerates documentation of tables and columns within the data catalog, facilitating downstream use.
Store and index structured and unstructured data within a common infrastructure, supporting high-throughput access.
Maintain detailed records of data lineage, provenance, and version history. These operations are automatically tracked, ensuring reproducibility and supporting compliance.
Reshape raw data into harmonized datasets optimized for exploratory and inferential analyses.
Integrate data from clinical and scientific systems, such as REDCap, OnCore, Cancer Registry, LIMS, molecular platforms (e.g., whole genome/exome sequencing, transcriptomics, proteomics), and imaging modalities (e.g., histology).
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Transform multimodal data into the Manifold OMOP-plus framework, a unified model that supports comprehensive querying and high-performance downstream applications.
