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reverse ETL

rev_etl
technology·Updated Jul 6, 2026

Definition

ISO-11179 Definition

The process of moving transformed, analytics-ready data from a data warehouse back into operational systems, CRMs, marketing platforms, or customer-facing applications, enabling data warehouse insights to power real-time operational workflows. In healthcare, reverse ETL is used to push risk scores from a warehouse back into care management platforms, send quality measure gap alerts to provider EHR systems, and populate member outreach lists in CRM systems from population health analytics outputs.

Standard Abbreviation

rev_etl

Category

technology

Production DDL — DIM_SYSTEM

DIM_SYSTEM.sql
CREATE OR REPLACE TABLE DIM_SYSTEM (
    sys_key         INTEGER       NOT NULL  -- surrogate key,
    sys_id          VARCHAR(50)   NOT NULL  -- system identifier,
    sys_nm          VARCHAR(200)  NOT NULL  -- system name,
    sys_type_cd     VARCHAR(50)             -- system type code,
    sys_vrsn        VARCHAR(50)             -- system version,
    vndr_nm         VARCHAR(200)            -- vendor name,
    intfc_type_cd   VARCHAR(50)             -- interface type code,
    intfc_proto_cd  VARCHAR(20)             -- interface protocol,
    env_cd          VARCHAR(20)             -- environment code,
    host_nm         VARCHAR(200)            -- hostname,
    ip_addr         VARCHAR(45)             -- IP address,
    sts_cd          VARCHAR(20)             -- status code,
    eff_dt          DATE          NOT NULL  -- effective date,
    exp_dt          DATE                    -- expiration date,
    rec_creat_dt    TIMESTAMP     NOT NULL  -- record created date
);

Standard Snowflake DDL for the canonical technology table. Convert to BigQuery or Databricks →

Why This Term Matters

Healthcare data terminology is foundational for any data engineer working in this industry. Precise understanding of standard terms enables accurate schema design, reduces downstream data quality issues, and ensures pipelines meet the regulatory and interoperability requirements imposed by HIPAA, HL7 FHIR, and CMS reporting frameworks. Without this foundation, even technically well-built pipelines produce data that fails validation when it reaches payers or regulators.

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