Case Study
"Querio has revolutionized how we handle data"
Querio
Dec 19, 2024
TL;DR;
Mercury Data struggled with inaccessible, complex data that slowed decision-making. Querio transformed their analytics with structured frameworks, ETL processes, and a semantic layer, enabling business users to access insights instantly. The result? 20x faster reporting, 95% accuracy, and true self-service analytics—reshaping data-driven decision-making.
20x
faster reporting cycles
95%
accuracy in data-driven insights
100%
self-service analytics for business users
About Mercury
Mercury Data is a customer-centric company that has grown in operational complexity over time. Founded before the advent of modern data tools like Querio, Mercury's data was messy and reporting required weeks of multi-stakeholder effort. The raw state of the data and its complex structure, built for software, made it virtually inaccessible for meaningful analysis. Hundreds of tables were organized around the objects required by their software, rather than the questions they needed to answer to efficiently run their business.
Size | Industry | Data stack |
|---|---|---|
Small | Customer-focused services | Google BigQuery |
Problem
Mercury Data faced significant challenges in accessing and analyzing their complex, raw data. Reporting processes were slow, taking weeks to gather and analyze data across multiple stakeholders. The data's structure, built for software operations, hindered meaningful analysis and decision-making.
Solution
Querio implemented a multi-phase transformation:
Understanding Business Nuance: Collaborated with Mercury's business leaders to map operational terminology and key business questions.
Assessing Existing Infrastructure: Worked with Mercury's engineering team to understand the current data storage solutions and identify opportunities for leveraging data for business objectives.
Architecting a New Framework: Designed a comprehensive plan to redefine Mercury's approach to analytics, creating a structure that streamlined data transformation and empowered the business team with a dynamic, intuitive analytics platform.
ETL Development and BigQuery Integration: Implemented an advanced Extract, Transform, Load (ETL) solution to translate raw data into a structured format optimized for analytical querying. Launched a Google BigQuery warehouse instance to host the transformed data.
Empowering Through Context: Developed a custom-built semantic layer and data catalog, mapping business terminology directly to data stored in BigQuery. This allowed non-technical personnel to navigate vast datasets using familiar terms, enabling self-service analytics.
Results
The implementation of Querio's solutions led to significant improvements:
20x faster reporting: Monthly reporting time reduced from 2 weeks to 30 minutes.
95% accuracy: Enhanced data-driven insights with high accuracy.
Self-service analytics: Business users can now access data directly without reliance on analysts or engineers.
Operational efficiency: Reduced headcount necessary to empower decision-makers with data.
"Querio has revolutionized how we handle data. What used to be a weeks-long process now takes minutes, and our teams feel empowered to make data-driven decisions on their own. The impact on our efficiency and accuracy is unparalleled."
