Construction Tech Case Study
Building a Scalable Analytics Foundation for Kojo Technologies
How Red Analytica helped Kojo modernize their analytics stack to support product insights, reporting reliability, and future growth.
The Challenge
Kojo, a fast-growing construction procurement and project management platform, was scaling rapidly across customers and projects. As data volumes increased, their existing analytics setup struggled to keep pace, leading to slower queries, inconsistent reporting, and limited visibility into product usage and customer behavior.
- Growing volumes of event, transaction, and operational data.
- Slow and unreliable analytics impacting business decisions.
- Limited ability to analyze product usage and customer trends.
The Solution
Red Analytica designed and implemented a modern lakehouse-based analytics platform on Databricks, focused on reliability, scalability, and analytics readiness. The solution unified multiple data sources into a single platform, enabling faster analysis and consistent reporting across teams.
- Designed a Databricks lakehouse using Delta tables for analytics workloads.
- Built reliable batch pipelines for product, usage, and operational data.
- Enabled consistent metrics and reporting for product and business teams.
Analytics Platform Architecture
A unified Databricks lakehouse architecture enabling data ingestion, transformation, and analytics at scale.
The Impact
~3–4×
Faster analytics query performance for core dashboards
Improved
Product and customer visibility across teams
Future-ready
Analytics platform designed to scale with business growth