Skip to content
PythonSQLETL

Marketing Analytics Data Pipeline

An end-to-end marketing analytics data pipeline that ingests, transforms and models campaign data for reporting.

Problem

Marketing data was scattered across campaign exports with no single source of truth, making channel-performance reporting slow and error-prone.

Solution

An end-to-end ETL pipeline that ingests raw campaign data, applies validated transformations, and lands it in query-ready tables for fast, consistent reporting.

Overview

Marketing teams often can’t answer “which channel is actually working?” quickly, because campaign data sits in disconnected exports rather than one queryable source.

How it works

This pipeline ingests raw campaign exports, applies a validated set of Python/SQL transformations (deduplication, type-casting, consistent campaign/channel naming), and lands the result in clean, query-ready tables. The transformation logic is written once and re-run on every new data drop, so reporting numbers stay consistent instead of drifting between manual spreadsheet edits.

Result

What used to be a manual, error-prone export-and-merge process becomes a repeatable pipeline that a BI tool or analyst can query directly.

More projects