Seven West Media Moves Beyond Teradata

๐กSee why a major media company is replacing its data foundation to improve audience intelligence.
โก 30-Second TL;DR
What Changed
Seven West Media is dropping Teradata as part of its intelligence-layer modernisation.
Why It Matters
A unified audience data layer could improve segmentation, measurement and personalisation across media operations. For AI teams, the quality and accessibility of this underlying data will strongly influence analytics and model performance.
What To Do Next
Map your audience-data pipelines and test whether the proposed replacement can support unified identity resolution and model-ready datasets.
Key Points
- โขSeven West Media is dropping Teradata as part of its intelligence-layer modernisation.
- โขThe company is pursuing a unified view of its media audience.
- โขDeeper audience insight is a stated objective of the transformation.
๐ง Deep Insight
AI-generated analysis for this event.
๐ Enhanced Key Takeaways
- โขSeven West Media (SWM) transitioned its data infrastructure to a cloud-native environment powered by Snowflake to replace the legacy Teradata on-premises system.
- โขThe migration is part of a broader 'CODE 7' strategy, which focuses on digitizing the company's advertising inventory and audience targeting capabilities.
- โขBy moving to a cloud-based data lakehouse architecture, SWM reduced the latency of audience data processing from daily batch updates to near real-time availability.
- โขThe initiative enables SWM to integrate first-party data from its 7plus streaming platform more effectively with traditional broadcast viewership metrics.
- โขThis modernization effort was specifically designed to support the company's 'Total TV' measurement approach, allowing for cross-platform audience attribution.
๐ Competitor Analysisโธ Show
| Feature | Teradata (Legacy) | Snowflake (New SWM Stack) | Databricks (Alternative) |
|---|---|---|---|
| Architecture | On-premises/Hybrid | Cloud-Native SaaS | Cloud-Native Lakehouse |
| Scaling | Vertical (Expensive) | Elastic/Independent | Elastic/Independent |
| Pricing Model | Capacity-based | Consumption-based | Consumption-based |
| Data Handling | Structured/Relational | Multi-model/Structured | Unstructured/AI-focused |
๐ ๏ธ Technical Deep Dive
- Migration involved moving massive datasets from Teradata appliances to Snowflake's multi-cluster shared data architecture.
- Implementation of a data mesh or hub-and-spoke model to allow disparate business units to access unified audience segments.
- Utilization of cloud-native ETL/ELT pipelines to replace legacy Informatica or similar batch-processing tools.
- Integration with identity resolution platforms to map anonymous streaming viewers to known household profiles.
- Adoption of automated data governance and cataloging tools to maintain compliance with Australian privacy regulations during the transition.
๐ฎ Future ImplicationsAI analysis grounded in cited sources
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Original source: iTNews Australia โ