From Raw Data to Real-Time Decisions

So much data, so little time. GoGrow's data engineering capabilities has allowed partners to bring their innovative solutions to life.

region

United States

TIMELINE

2022 - Present

Main Technologies

SQL

,

Python

,

Growth Nirvana Dashboard

CAPABILITIES

Data Engineering

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About Growth Nirvana

With over 150 data source integrations and a no-code interface, Growth Nirvana gives marketers and agencies the power to automate reports, unify performance metrics, and uncover actionable insights in record time. Their mission is simple: eliminate the friction between ad platforms and analysis so users can focus on outcomes, not data wrangling. The platform has become a go-to for advertisers looking to move fast without giving up visibility. With Growth Nirvana, teams can customize dashboards, calculate revenue impact metrics, and roll out white-labeled reports, all without touching a line of SQL.

The Problem

Growth Nirvana was in the market for a development partern with Data Engineering capabilities in order to develop their cutting-edge tools to their growing number of clients. That's where we came in.

The Solution

We've provided Growth Nirvana with data analysts and data engineers to work on their analytics platform. Our team created an internal tool that enables SQL transformations on data ingested from external integrations such as Shopify, Google Analytics, Google Ads, Facebook Ads, among others. By connecting their data warehouse to over 300 data sources, they can now build real-time data pipelines and SQL transformations that power dashboards and full-funnel reporting in just minutes. In addition to providing pre-built reports based on industry best practices and standard requirements, we've also worked on their ability to offer tailored data engineering services. These include custom models such as multi-touch attribution analysis, GA4 audits, and Google Tag Manager implementations.

Conclusion

Growth Nirvana now runs on powerful, real-time data pipelines that drive faster insights and smarter decisions. With streamlined data engineering and custom analytics capabilities in place, their team can focus on delivering value to clients while giving users instant access to clear, actionable performance metrics.

TAGS

Data Analytics

Data Analytics

SQL

Python

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