SAP ECC Cloud Composer

Canadian clothing retailer accelerates data insights with Enterprise Data Platform QuickStart for Google Cloud

by Rohith
1 min read
Jun 23, 2022

Overview

Industries

Retail & E-commerce

Locations:

Canada

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.

What we did

Pythian fast-tracked important store analytics with a proprietary Enterprise Data Platform QuickStart for Google Cloud solution. In just a few weeks, the Pythian team:

  • Deployed a cloud-based data lake using Google Cloud and Google Big Query
  • Created a series of pipelines to support client data sets from multiple sources
  • Built custom reports and dashboards to analyze important metrics

Business need

As the COVID-19 pandemic impacted its supply chain and slowed foot traffic at its stores, the Canadian clothing retailer realized it needed stronger analytics to guide its strategy. However, its legacy system-an on-premises SQL Server environment-made it nearly impossible to achieve its business intelligence goals.

 
 
 

Technologies used

 
  • Google BigQuery
  • Google Cloud Build
  • Google Cloud Composer
  • Google Cloud Functions
  • Google Cloud SQL
  • Google Cloud Storage
  • Google Dataproc
  • Google Pub/Sub
 

Enterprise Technology Areas 

 
  • Marketing Analytics
  • Data Lakes

Key Outcomes

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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