Customizable In-house ETL Tool for Retail Operation Management

A shift in focus to eCommerce caused many data processing challenges for a major American retailer. Developing an in-house ETL tool and leveraging Google BigQuery improved adaptability, scalability, and productivity, even while reducing the overall cost of retail operations.

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    Executive Summary

    A well-known American department store chain offers a wide range of products including clothing, accessories, beauty products, home goods, and more. Amid the pandemic, the client shifted focus to their eCommerce channel, resulting in exponential growth.

    Relying on third-party tools for data processing posed challenges with scale, speed, cost, and personalization. So, they embarked on developing an in-house ETL tool for greater control and customization. By adopting Google Big Query and leveraging cloud-based solutions, Factspan team improved data processing efficiency and achieved significant reductions in both query count and data processing execution time by around 50%.

    Additionally, the data engineering teams experienced a 30% increase in productivity using a simple SQL programming language. The client estimates annual 20% cost savings by eliminating the need for external vendor support.

    Project Highlights
    • Developed a proprietary ETL tool that offers full customization control and cost savings of around 20%.
    • Greater control and flexibility to customize the tool according to specific needs, workflows and data sources.
    • The in-house ETL tool streamlined query efficiency – 30% productivity improvement and 50% reduction in execution time.
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