Transforming Data Quality for Ad Optimization & Marketing Analytics | Datagaps Case Study

Описание: Explore how a global marketing analytics and ad optimization company transformed data quality operations to support real-time decisions and campaign execution using Datagaps DataOps Suite.

Challenges: Processing 50TB+ daily from 10+ sources; scalability issues for small data team; schema variability and new source onboarding delays; inconsistencies impacting ad performance; lack of traceability for root cause analysis.

Solutions: Automated DQ pipelines with real-time validation for schema drift, freshness, and format consistency; JIRA integration for issue tracking; automated onboarding for new feeds; end-to-end data lineage and observability.

Results: Validation time reduced from hours to minutes; real-time anomaly alerts; handled 10+ sources and 50TB/day; 75% data assurance team reduction (1 member manages all); rapid new campaign support.

Impact: Faster, accurate ad targeting; efficient analytics; increased stakeholder trust; scalable without headcount growth; shifted from manual/reactive to real-time automated process.

A must-watch for marketing analytics, ad tech, and data teams handling high-volume feeds!

Key Moments:
00:00 - Introduction & Case Study Overview
00:21 - Challenges: 50TB Daily Processing & Scalability
00:24 - 10+ Sources & Schema Variability
00:31 - Inconsistencies & Ad Performance Impacts
00:45 - Lack of Traceability
00:53 - Solutions: DataOps Suite DQ Pipelines
01:05 - Real-Time Validation & Schema Drift Detection
01:14 - JIRA Integration & Automated Onboarding
01:26 - Data Lineage & Observability
01:40 - Key Metrics: Hours to Minutes Validation
01:52 - 75% Team Reduction & 50TB Handling
02:02 - Final Business Impact
02:13 - Faster Ad Targeting & Trust Boost
02:20 - Scalable Automated Process
02:37 - Contact & Free Demo QR Code
02:42 - Thank You

Learn More / Case Study: https://www.datagaps.com/case-study/t...

Contact: [email protected]
Scan the QR code in the video for a free demo!

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