Build trusted analytics and AI-ready tables faster with medallion architecture in Oracle AI Data Platform Workbench.
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In this demo, you learn how medallion architecture organizes and refines data in Oracle AI Data Platform Workbench using bronze, silver, and gold layers in a data lakehouse pattern. The walkthrough starts by creating a Finance catalog and setting up bronze, silver, and gold schemas to structure the pipeline from raw ingestion to curated business outputs.
You begin in the bronze layer by ingesting raw bank transaction data, such as deposits, withdrawals, and transfers, preserving source structure for traceability and auditability. You then move to the silver layer to prepare analytics-ready data by cleaning, validating, deduplicating, and enriching records with derived date attributes such as month, day, and day of week, while filtering invalid or corrupted records like missing amounts or IDs.
Finally, you build the gold layer with curated business datasets designed for dashboards, advanced analytics, and machine learning. The demo shows how to create monthly aggregations such as month, year, total amount, average amount, and average risk scores, validate the output, and load the results. You also see how gold data supports feature engineering and model training, including preparing fraud detection data and training a predictive machine learning model.
0-0:28 Intro to Medallion Architecture
0:28-1:25 Bronze Layer
1:26-2:05 Silver Layer
2:05 Gold Layer
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