DataRopes.ai Navbar
Ready to start and grow your business bigger and win customers forever? Check it out
Project Duration
5 months
Client Industry
Saas and Tech

Target Markets
North America

Crowdbotics

Business Intelligence Platform for Development Services Marketplace

Technology Stack

No items found.

Client Overview

Challenges in Modeling Subscription and Business Metrics

Crowdbotics is a platform that connects clients with freelance software development teams, offering end-to-end development services through a managed marketplace model. With thousands of active projects and globally distributed teams, the company focuses on delivering scalable, high-quality apps while ensuring operational visibility for both internal teams and clients.

Solutions Delivered

Automated multi-source data ingestion at scale Centralized, DBT-modeled warehouse in BigQuery Role-based dashboards for actionable insights

Scalable analytics with GitHub integration

Team Composition

Data Engineer

Data Analyst

Cloud Solutions

Architect Project Manager

Engagement Type

Hourly Base Contract

Key Challenges

Key Challenges in Project and Performance Visibility

Data Fragmentation

Disconnected systems (Heroku, Stripe, HubSpot, Toggl, Sheets) lacked unified reporting

Operational Blind Spots

No single view into project health, team performance, or financial insights

Scalability Issues

Manual reporting didn’t scale with 5000+ active projects and 1000+ contributors

Strategic Roadmap

To support enterprise-scale operations, we must centralize fragmented data from platforms like Heroku, Stripe, HubSpot, Toggl, and Sheets into a unified model. Automating daily ingestion and transformation for 5000+ projects is critical for timely insights. Understanding stakeholder-specific dashboard needs—PMs, executives, and recruiters—ensures relevance. Finally, enabling continuous deployment and version control via GitHub will ensure scalability, maintainability, and agility as the data architecture evolves.

Read More
Read Less
To unify project, financial, and operational data at scale, we built a modular data model using DBT, fully integrated with GitHub for version control and continuous deployment. Scalable ETL pipelines were developed to automate ingestion from Stripe, Heroku, HubSpot, Toggl, and Google Sheets, ensuring consistent daily updates.

Execution Approach

Modular, Scalable Architecture for Unified Project Intelligence

To unify project, financial, and operational data at scale, we built a modular data model using DBT, fully integrated with GitHub for version control and continuous deployment. Scalable ETL pipelines were developed to automate ingestion from Stripe, Heroku, HubSpot, Toggl, and Google Sheets, ensuring consistent daily updates.
All data was centralized and modeled in BigQuery to create a reliable, queryable source of truth.
On top of this architecture, we delivered customized Looker dashboards tailored to key stakeholders—including executives, project managers, and talent ops—providing real-time insights into project health, team performance, and financial metrics, ultimately enabling faster, data-driven decision-making across the organization.

BUSINESS IMPACT

Comprehensive Project Oversight
Data-driven decisions supported by centralized, real-time visibility into campaign performance.
Financial and Operational Clarity
Significant reduction in time spent on manual reporting tasks.
Recruitment Efficiency
Detailed analytics broken down by region for better insights.
Accelerated Decision-Making
Enhanced optimization throughout the entire lifecycle.

25%

reduction in operational costs through automated workflows


15%

increase in team productivity via better project tracking


 30%

faster issue resolution from enhanced project health monitoring