Pythian deployed a data lake in Google Cloud and Google BigQuery, created ETL pipelines, and built custom reports and dashboards for a single use case to analyze two years of customer data in seven weeks.
Retail & E-commerceLocations:
A Canadian clothing retailer needed more robust analytics to guide its strategy during the pandemic, but its legacy SQL Server environment made accessing data from multiple sources difficult. Using a proprietary Enterprise Data Platform QuickStart for Google Cloud framework, Pythian fast-tracked the retailer’s move to the cloud. In a matter of weeks, Pythian deployed a data lake in Google Cloud and Google BigQuery, created ETL pipelines, and built custom reports and dashboards to analyze two years of customer, location, and purchase data. The internal marketing and BI teams can now “self-serve” the insights they need; the retailer has the right foundation to expand data access and leverage machine learning and AI capabilities.
This successful pilot gives this retailer access to two years of customer, location, and purchasing data to drive immediate decision-making. It establishes a strong foundation for future data analytics, including the retailer’s goal of leveraging machine learning and artificial intelligence capabilities from Google for marketing analytics.
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