Data Platforms
Tariff Master List Ingestion & Azure SQL History Pipeline
Master-data ingestion pipeline that loads tariff files into Azure SQL with controlled validation, staging, stored-procedure upserts, and current-plus-history data modeling.
Data platform command view
Tariff Master List Ingestion & Azure SQL History Pipeline
Controlled tariff-file intake, validation, staging, stored-procedure upserts, and current/history SQL publication
Receive
Files / Batches
Map
Columns / Schema
Validate
Dates / Rates
Upsert
Stage / Merge
Publish
Current / History
Validation and publish checks
Load controlsPublished data layers
Operational outputsCurrent tariff view
Latest active tariff state for downstream operational use
History tariff view
Effective-dated record history for change review and traceability
Load batch trail
Supports auditing, replay review, and pipeline support analysis
Source files
Tariff Masters
Target
Azure SQL
Model
Current + History
Controls
Validated
Business problem
Tariff data needed more than a simple file load. The process required controlled validation, reliable SQL loading, and a way to preserve historical changes instead of replacing the prior state each time a new file arrived.
Without a structured ingestion pattern, tariff updates could become hard to trace, hard to audit, and harder to reuse in downstream analytics. The workflow needed staging, cleanup, and history-aware publication so the data could support operations with more confidence.
System built
Built local / Azure Blob ingestion, column mapping, rate cleanup, field validation, staging-table loads, stored-procedure upserts, and current/history views for tariff master data.
The result is a pipeline that behaves like an operational data platform rather than a one-time import. It accepts source files, shapes them through controlled steps, and publishes SQL outputs designed for reuse, support, and historical review.
Review controls
Signals reviewed
The pipeline checks source readiness, schema alignment, field quality, rate normalization, upsert readiness, and publication status so tariff data can be trusted as it moves into downstream reporting and operational analysis.
Processing workflow
How it works
Receive
Collect tariff source files from controlled intake locations and prepare them for processing.
The workflow starts by treating the source file as an operational input instead of a one-off spreadsheet, making the load more repeatable and more reliable.
Map
Map incoming columns into the target schema and align source fields with expected SQL structures.
This reduces fragility when source files shift slightly and helps the pipeline keep a stable contract between file layout and database design.
Validate
Apply field checks, date checks, rate cleanup, and row-level validation before records move into SQL.
The validation layer protects downstream tables from malformed rows, missing values, and tariff records that are not ready for controlled publication.
Upsert
Load clean rows into staging tables and run stored-procedure logic to merge records into current and history structures.
The upsert pattern preserves a clean operational table while also maintaining a more useful historical trace of tariff changes over time.
Publish
Expose usable SQL outputs through current and history views for reporting, audits, and downstream analytics.
The final layer turns the ingestion process into a dependable data asset rather than a one-time file load.
System layers
What the pipeline coordinates
Ingestion control
Handles source-file intake, batch awareness, and load preparation so the pipeline starts from a repeatable operational entry point.
Validation layer
Checks required fields, normalizes rate and date values, and filters out rows that are not ready for SQL publication.
Staging + upsert
Uses staging tables and stored procedures to control how source data becomes current-state and history-state records.
History model
Maintains current and historical views so tariff changes can be reviewed over time instead of being overwritten and lost.
Impact signals
What the pipeline improved
Effective-dated tariff history instead of overwrite-only loading
Staging-to-current pattern for safer SQL publication
Stored-procedure upsert control
Batch traceability for review and support
Cleaner downstream reporting and analytical reuse
Operational value
Why this platform matters
More controlled ingestion
Turns tariff loading into a governed process with staging, validation, and publication layers rather than a fragile spreadsheet import.
Better historical traceability
Preserves change history so tariff updates can be reviewed across time instead of only seeing the latest version.
Safer SQL delivery
Separates raw intake, staging, and published outputs so downstream users can trust the current and history views more confidently.
Stronger business reuse
Makes tariff data easier to support in reporting, audits, pricing analysis, and future automation work.
Why this project matters
Master-data pipelines become far more valuable when they preserve both operational usability and change history.
This project shows how tariff ingestion can move beyond raw file loading. By combining source intake, schema mapping, validation, staging, and stored-procedure upserts, the pipeline creates a controlled path from spreadsheet-like source files into reliable SQL data assets.
The current-and-history design is especially important because it preserves business context over time. Instead of only seeing the latest tariff state, the platform helps support auditing, change review, and downstream analysis built on a more trustworthy historical foundation.
Confidentiality note
Visuals and descriptions are sanitized conceptual representations. They do not expose private company data, tariff source files, raw rate tables, customer records, internal pricing details, Azure SQL credentials, proprietary stored procedures, or operational screenshots.