Mayvenn case study

Styling Data Pipelines for Analytics Success at Mayvenn

Mayvenn, with a mission to provide high-quality beauty products with an unparalleled shopping experience, uses world-class technology to empower beauty professionals by enabling them to grow their business, while providing them and their clients with exceptional customer support—all backed by a robust and growing data analytics backbone.

Mayvenn built their business on providing superior experiences for their stylist network as well as the clients those stylists serve, the basis of which relies on extensive data pipelines that covered a variety of customer and marketing data. 

With increasing, disparate data streams, the Mayvenn analytics team set out to find a data orchestration solution that enabled them to handle the vast majority of data ingest and transformations while also delivering the ability to rapidly iterate on ETL without requiring help from the engineering team. This is what led the Mayvenn team to the Ascend Unified Data Engineering Platform.

 

“To a large extent, we had the technical skillset with SQL and PySpark to be able to do many of the tasks we required; we just didn’t necessarily understand the architecture of how it was being transformed through the pipeline.

“With the Ascend Platform’s visual and interactive UI, everybody on the team is now comfortable with being able to do the vast majority of the transforms that we need.”

Geoff Aoyagi, Senior Director of Data and Analytics at Mayvenn

While the ability to rapidly iterate on ETL to create and deploy modern data pipelines is one of the key benefits that Mayvenn has achieved with Ascend, it’s not the only one. Check out the case study to learn more.
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