150+ Data Sources, 1 Intelligence Platform: An Automotive Brand's Data Unification Story
An enterprise-scale Data Lakehouse and AI analytics platform that unified data across 50+ markets and powered personalization across the entire customer lifecycle.
A leading global automotive company wanted to turn fragmented data across markets, dealers, and connected vehicles into real-time enterprise intelligence. Binariq designed and implemented an enterprise-scale Data Lakehouse and AI analytics platform that unified data across 50+ markets, enabled predictive insights, and powered personalization across the entire customer lifecycle.
What made this hard.
- Customer, dealer, connected-vehicle, and marketing data spread across disconnected platforms.
- No unified customer view, making consistent personalization impossible.
- Regional reporting silos limiting visibility into journeys, operations, and marketing effectiveness.
- Online and offline interactions that couldn't be connected into a single picture.
- Connected-vehicle data sitting underutilized, with no path to predictive maintenance or usage intelligence.
How we engineered the solution.
Azure data lakehouse consolidating customer, dealer, IoT, CRM, and marketing data.
Real-time ingestion with Synapse, Data Factory, Event Hubs, and Stream Analytics.
Customer 360 on Salesforce CDP for unified profiles, segmentation, and campaigns.
ML forecasting and Power BI dashboards standardized across 50+ markets.
The biggest shift wasn't collecting more data. It was connecting it. By consolidating every customer, dealer, vehicle, and marketing signal into one governed platform, the organization moved from reactive regional reporting to proactive global intelligence.
What this engagement proved.
Meaningful AI transformation requires a unified, governed data foundation first.
Real-time analytics become significantly more valuable when customer, operational, and IoT data live in one ecosystem.
Customer 360 delivers the greatest impact when paired with predictive analytics and activation.
Standardizing analytics across markets improves governance, consistency, and enterprise-wide decision-making.
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