Data Pipeline Modernization for E-commerce Giant

How we helped a global retail e-commerce company transform their data infrastructure for real-time analytics and improved customer experiences

Industry

Retail E-commerce

Challenge

Outdated batch-processing data architecture causing delays in analytics and decision-making

Solution

Modern, scalable data pipeline with real-time processing capabilities

The Challenge

Our client, a leading global e-commerce retailer with millions of customers across multiple countries, was struggling with an outdated data infrastructure that couldn't keep pace with their rapid growth. Their legacy ETL processes were designed for batch processing, resulting in significant data latency issues that hindered their ability to make timely business decisions.

Key challenges included:

  • Data latency of 8-12 hours, making real-time inventory and pricing decisions impossible
  • Siloed data across multiple systems leading to inconsistent analytics
  • Limited scalability during peak shopping periods (e.g., holiday seasons)
  • Growing compliance requirements around customer data storage and processing
  • Complex and fragile data pipelines requiring substantial maintenance

Our Approach

We developed a comprehensive data modernization strategy focused on replacing batch-oriented processes with a real-time, event-driven architecture. Our approach emphasized scalability, governance, and actionable insights to support the client's ambitious growth targets.

Technologies Implemented

Apache Airflow
Apache Spark
Snowflake
Looker
Kafka

Key Components of Our Solution:

  • Replaced legacy ETL processes with Apache Airflow for workflow orchestration and Apache Spark for distributed data processing
  • Implemented event-streaming architecture using Apache Kafka to enable real-time data flows
  • Migrated data warehouse to Snowflake, improving scalability and enhancing data governance capabilities
  • Built self-service analytics dashboards with Looker, empowering business users to access insights without IT assistance
  • Integrated CI/CD for data models, allowing for rapid iteration and testing of analytics solutions
  • Implemented comprehensive data governance framework to ensure compliance with GDPR and other regulations

The data pipeline modernization by Codewise Analytics has transformed how we operate. We've gone from waiting hours for inventory and sales reports to having real-time insights at our fingertips. This has directly impacted our bottom line through better inventory planning and more responsive pricing strategies.

— VP of Data and Analytics, Global E-commerce Retailer

Results

Our data pipeline modernization delivered significant improvements in analytics capabilities, operational efficiency, and business agility:

70%
Reduction in Data Latency
3x
Faster Query Performance
40%
Lower Infrastructure Costs
12%
Increase in Inventory Efficiency

Results

The result was faster business insights, improved reliability, and operational efficiency. The client was able to leverage their data assets more effectively, leading to better customer experiences and increased revenue opportunities.

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