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Data Orchestration Platform for AdTech
  1. case
  2. Data Orchestration Platform for AdTech

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Data Orchestration Platform for AdTech

lineate.com
Advertising & marketing
Media
Information technology

Challenges in Modern AdTech Data Management

AdTech companies struggle with managing massive data volumes, ensuring compliance with evolving privacy regulations, and activating first-party data effectively. Current solutions often rely on third-party platforms, lack automation, and fail to provide real-time insights for campaign optimization.

About the Client

Technology consulting firm specializing in AdTech data solutions with 10+ years of experience

Key Goals for Data Transformation

  • Create a unified data orchestration platform for first-party data activation
  • Implement automated data quality improvement using AI/ML
  • Establish real-time data aggregation from diverse sources
  • Ensure compliance with privacy regulations through consent management
  • Reduce dependency on third-party adtech platforms

Core System Capabilities

  • Multi-source data unification (IoT, digital platforms, CRM)
  • Real-time data aggregation engine
  • AI-powered predictive analytics for ad performance forecasting
  • Automated data classification and mapping
  • Privacy compliance framework with consent management
  • Programmatic audience segmentation engine

Technology Stack Requirements

Apache Kafka for real-time data streaming
Spark for big data processing
TensorFlow/PyTorch for ML models
AWS/GCP cloud infrastructure
Snowflake/BigQuery for data warehousing

System Integration Needs

  • DSP/SSP platforms
  • CRM systems (Salesforce, HubSpot)
  • IoT device APIs
  • Ad servers (DFP, Sizmek)
  • Data management platforms (DMPs)

Operational Requirements

  • Horizontal scalability for petabyte-scale data
  • 99.99% uptime with active-active architecture
  • Sub-50ms latency for real-time bidding
  • GDPR/CCPA compliance framework
  • Automated failover and disaster recovery

Expected Business Outcomes

Implementation will enable 300% faster time-to-insight for campaign optimization, reduce data processing costs by 40% through automation, improve targeting accuracy by 60% using ML models, and ensure full compliance with global privacy regulations. The platform will support handling 10B+ daily ad impressions with reduced third-party dependency.

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