Customer Story

PDPAOLA Stands out in a Crowded eCommerce Market with Google Cloud Dataprep



Industry: Retail

Data Stack: Shopify, Google Cloud, Dataprep, BigQuery, Stitch, Data Studio

Region: Global

1 Employee

Builds and automates data pipelines

Reduce Spend

Without sacrificing scale and reduces downtime

Core Challenges

PDPAOLA is an online jewelry company with hundreds of unique, high-quality products. While its underlying Shopify eCommerce platform provides helpful analytics about the products’ high-level profit margins, PDPAOLA knew that bringing in huge quantities of data to uncover more granular insights like net margins or contribution margins was the only way that it could differentiate itself from the market in the long run. But as PDPAOLA began to build out data pipelines using SQL on Google Cloud, it quickly realized that it would reach a scalability limit. Hiring other SQL developers and training those developers on the company’s unique processes would require lots of time and resourcing spend. PDPAOLA needed a platform that would increase automation so that it could scale without added spend.

How Cloud Dataprep Solved this Problem

PDPAOLA selected Google Cloud Dataprep because it natively integrates with the Google Cloud Platform, allowing the team to quickly begin migrating its work over to Dataprep. Now, the team works with Stitch to ingest a variety of data sources, Dataprep to build pipelines that clean and structure diverse data in BigQuery, and Google Data Studio for data visualization and reporting. Due to Dataprep’s automation, PDPAOLA has been able to quickly advance analytics efforts without hiring new employees. And even when new employees are hired on, Dataprep will allow them to get up to speed immediately through its visual data flows that depict exactly where data is coming from and how it’s being transformed. PDPAOLA is using Dataprep to fuel Data Studio dashboards that report advanced insights down to each individual SKU, which allow for smarter and more precise business decisions.



Increased Scalability

With Dataprep, just one employee can build and automate many different data pipelines, while visual data flows allow new employees to get up to speed quickly on data pipeline strategy.

Reduced Spend

Not only does Dataprep allow PDPAOLA to slow its hiring without sacrificing scale, but it also reduces downtime (and the money lost along with it), with the ability to visually identify and remediate issues fast.

More Granular Insights

Dataprep allows PDPAOLA to easily transform many different diverse data sources, such as shipping costs, product information, or Google Analytics, in order to build robust reporting in Data Studio.

Company Background

PDPAOLA Jewelry, founded in 2014, is the result of a balanced combination of the creative and business worlds, working together towards the disruption of the jewelry industry.



With Dataprep, you don’t need to have a large team. In the past, you needed to have a lot of developers or Excel experts. Now they’re no longer required, which translates into payroll savings for the company. There’s also a huge amount of flexibility—if something breaks, it’s a lot easier to troubleshoot a Dataprep flow than it is to troubleshoot multiple queries, especially if you have multiple developers with different coding styles.


Joel Chaparro Benaim, Data Scientist



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