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.