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Ascend.io > Case Studies > Styling Data Pipelines for Analytics Success at Mayvenn
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Styling Data Pipelines for Analytics Success at Mayvenn

Technology Category
  • Analytics & Modeling - Real Time Analytics
  • Infrastructure as a Service (IaaS) - Cloud Storage Services
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Consumer Goods
  • Retail
Applicable Functions
  • Business Operation
  • Sales & Marketing
Use Cases
  • Demand Planning & Forecasting
  • Predictive Quality Analytics
  • Supply Chain Visibility
Services
  • Cloud Planning, Design & Implementation Services
  • Data Science Services
The Challenge
Mayvenn, a company that provides high-quality beauty products and aims to connect customers with the right stylists, relies heavily on data for its operations. The company moves a variety of data, including ad and marketing spend, email, text, and customer service data, from Amazon S3 to Amazon Redshift using Python for analysis and into Looker for reporting. However, the company faced challenges with its previous data orchestration tool, Alooma, which hindered fast iteration of ETLT. The data team at Mayvenn often found themselves blocked on projects due to dependency on the engineering team, which often had a full queue.
About The Customer
Mayvenn is a highly data-driven company that serves both stylists and their clients. The company's mission is to provide high-quality beauty products with an unparalleled shopping experience. To achieve this, Mayvenn uses data to empower hairstylists and salon professionals while also providing the stylists’ customers with stellar experiences. The company built a robust, data-centric platform to connect the right customers with the right stylists and the right experiences. In addition to this, the platform also powers the growing business with comprehensive data analytics pipelines.
The Solution
Mayvenn implemented the Ascend Unified Data Engineering Platform to overcome the challenges they faced with data orchestration. This platform empowered the data analysts at Mayvenn to make changes quickly and cost-effectively without relying on other teams. Within a month, the data analysts were working deeply in the Ascend platform, which accelerated their pipeline and gave them more independence. The Ascend platform also provided a visual flow that made it easy to see every step of the transformations. In addition, Ascend's customer support team was always available to respond to any questions or support requests.
Operational Impact
  • The Ascend Unified Data Engineering Platform enabled the data analysts at Mayvenn to make changes to data pipelines rapidly and cost-effectively.
  • The Ascend platform provided a visual flow that made it easy to see every step of the transformations.
  • Ascend's customer support team was always available to respond to any questions or support requests.
Quantitative Benefit
  • Data analysts were able to work deeply in the Ascend Unified Data Engineering Platform within a month, significantly accelerating their pipeline.

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