The dbt project converts raw data from a database into a dimensional model, preparing customer and purchase data for analytics.
The data pipeline is composed of multiple stages, beginning with the ingestion of raw data through dbt seed.
From these raw data sources, several staging tables are generated: stg_customers
, stg_products
, and stg_purchases
. These tables hold cleaned and structured data on customers, products, and transactions, respectively, which supports analysis and reporting. The customer_demographics
table summarizes customer data such as age and nationality, facilitating demographic analysis and targeted marketing efforts. The product_popularity
table aggregates data on product purchase frequency, delivering insights into product demand to inform inventory and marketing strategies. Finally, the purchase_patterns
table examines customer purchase behavior over time, aiding in understanding buying trends and optimizing the customer journey.
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