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Solution2024LTK (RewardStyle)

Marketing tag data deduplication

Rebuilt trust in marketing tag tables — traced lineage upstream, then fixed the load strategy that compounded duplicates downstream.

Problem

Tag-based tables were heavily inflated with duplicates from historical data modeling. Incremental loads kept compounding bad rows until marketing analytics on campaign and canvas tags was untrustworthy.

Approach

Trace lineage from upstream tables to find where duplicates entered, then change the Airflow-orchestrated downstream loads from incremental merge to full overwrite so row counts stay reliable for every consuming team.

Architecture

Marketing data pipeline

Full-overwrite upstream; Airflow downstream with full overwrite on tag tables.

Drag nodes to explore the flow

Load strategy

Why incremental downstream kept inflating duplicates.

Before

Incremental merges on tag tables compounded duplicate rows even when upstream tables only had a handful of bad records.

After

Full overwrite downstream aligned with upstream full-refresh semantics — reliable row counts for marketing and CS analytics.

Solution highlights

Lineage first

Traced upstream sources through Airflow-orchestrated loads to isolate where duplicates compounded.

Full overwrite downstream

Tag tables switched from incremental merge to full overwrite, matching upstream refresh semantics.

Documented load behavior

Upstream vs downstream semantics written down so the fix held for every consuming team.

Trust restored

Reliable row counts for marketing and customer-success analytics.

BrazeAirflowData quality