Ascend.io Case Studies Supercharging Time to Analysis at Harry’s

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	Supercharging Time to Analysis at Harry’s Ascend.io

Supercharging Time to Analysis at Harry’s

Ascend.io

Technology Category	Analytics & Modeling - Real Time Analytics Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Retail
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Demand Planning & Forecasting Supply Chain Visibility
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	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. Read More
About Customer	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. Read More
Solution	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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Retail

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Demand Planning & Forecasting

Supply Chain Visibility

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

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.

About Customer

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.

Solution

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.

Impact #1	10X the speed to ingest, transform and pipe data into Looker using Ascend.io
Impact #2	Accelerated the ramp time for data analysts using Ascend.io’s flexible UI
Impact #3	Accelerated and simplified iteration on data feeds to get faster, more actionable analysis within Looker.

Impact #1

10X the speed to ingest, transform and pipe data into Looker using Ascend.io

Impact #2

Accelerated the ramp time for data analysts using Ascend.io’s flexible UI

Impact #3

Accelerated and simplified iteration on data feeds to get faster, more actionable analysis within Looker.

Benefit #1	10X the speed to ingest, transform and pipe data into Looker using Ascend.io

Benefit #1

10X the speed to ingest, transform and pipe data into Looker using Ascend.io

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Overview

Supercharging Time to Analysis at Harry’s

Operational Impact

Quantitative Benefit