data lakehouse table format
lkhs_tbl_fmtDefinition
ISO-11179 Definition
An open storage specification that defines how data files, metadata, and transaction logs are organized in cloud object storage to support ACID transactions, schema evolution, and time travel queries from multiple query engines. The three major competing table formats are Delta Lake, Apache Iceberg, and Apache Hudi, each offering different trade-offs in terms of ecosystem compatibility, compaction efficiency, and merge-on-read versus copy-on-write strategies for healthcare data platform architecture decisions.
Standard Abbreviation
lkhs_tbl_fmt
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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