full refresh load
full_refreshDefinition
ISO-11179 Definition
A data pipeline pattern that truncates and completely reloads a target table from the source on each execution, guaranteeing accuracy at the cost of higher compute and I/O compared to incremental loading. Full refreshes are appropriate in healthcare data engineering for small reference tables such as ICD-10 code sets, provider taxonomy codes, and ZIP-to-county crosswalks where the entire dataset is small enough to reload efficiently and source deletion semantics make incremental approaches complex.
Standard Abbreviation
full_refresh
Category
Production DDL — DIM_SYSTEM
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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