Making urban mobility effortless with smarter parking solutions
Estapar, Brazil's largest parking network, unified over 600 data sources on the Databricks Data + AI Platform, using AI/BI Genie for self-service analytics and Spark Declarative Pipelines for automation, cutting license plate analysis from three days to real time and delivering a 20x productivity boost.
Overview
Estapar, Brazil's largest parking network, unified over 600 data sources on the Databricks Data + AI Platform, using AI/BI Genie for self-service analytics and Spark Declarative Pipelines for automation, cutting license plate analysis from three days to real time and delivering a 20x productivity boost.
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Inspect the highlighted sourceThe challenge
As Estapar grew, some areas had a fragmented data landscape with distinct databases creating silos, complex data pipelines across different fronts made generating insights time-consuming and resource-intensive, and business teams heavily relied on the data team to access and analyze information, limiting agility in decision-making.
The solution
Estapar consolidated all transactional and customer data into a unified platform on the Databricks Data + AI Platform, introduced AI/BI Genie data rooms so business users could independently access and analyze data without technical expertise, implemented Spark Declarative Pipelines to automate data pipelines, integrated Unity Catalog for data governance, and leveraged MLflow to simplify and accelerate the development and deployment of AI models, while developing an AI-driven agent to improve customer support through the Zul+ app.
Reported business value
Estapar reduced data processing time from three days to real-time, improved demand forecasting accuracy, and empowered business teams with self-service analytics, unifying 600+ data sources for more holistic decision-making and delivering a 20x productivity boost, doing the work of 100+ people with just 5.
Sources
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