Supercharging Time to Analysis at Harry’s
公司规模
1,000+
地区
- America
国家
- United States
产品
- Ascend.io
- Looker
技术栈
- Data Orchestration
- Business Intelligence
- Data Analytics
实施规模
- Enterprise-wide Deployment
影响指标
- Digital Expertise
- Productivity Improvements
技术
- 分析与建模 - 实时分析
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 零售
适用功能
- 商业运营
- 销售与市场营销
用例
- 需求计划与预测
- 供应链可见性(SCV)
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
Harry’s, launched in 2012, is a direct-to-consumer industry leader with a growing presence in online retail, and brick and mortar markets. The company has a revolutionary Direct to Consumer (DTC) model that is now widely emulated. The growing diversity of product lines, retail outlets, and customers has led to an explosion of new, disparate data feeds that are critical for timely and actionable business insights. The company uses Looker as its business intelligence and analytics tool of choice. The data science team at Harry's undertook an effort to expedite ingesting, transforming, and delivering these data feeds into a robust shared data model that connects all brand information across every retail delivery model.
挑战
Harry’s, a leader in the direct-to-consumer industry, faced a challenge with the explosion of new, disparate data feeds due to the diversity of product lines, retail outlets, and customers. The data science team needed to expedite the process of ingesting, transforming, and delivering these data feeds into a robust shared data model that connects all brand information across every retail delivery model. The retail analytics team needed a faster, simpler way to get new analytics up and running, and a platform to ingest and transform these disparate data feeds in a low-code sandbox environment. With a current ecosystem of mostly homegrown and open source solutions that rely on a heavily burdened data engineering team, it could take weeks to get new, critical retail data sources connected to Looker, the company’s business intelligence and analytics tool of choice.
解决方案
To accelerate the access to and bolster the analytics of new and existing data feeds, Harry’s head of analytics, Pooja Modi, and data analyst, William Knighting, spearheaded an initiative to deploy a new data orchestration platform that could reach securely across all their data infrastructure, and also work seamlessly with Looker. They chose Ascend.io for this purpose. Ascend.io offered a faster, simpler way to get new analytics up and running, and a platform to ingest and transform these disparate data feeds in a low-code sandbox environment. The flexibility offered with Ascend.io provides an ease of use that has been critical to accelerating the use of Harry’s data and analytics.
运营影响
数量效益
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