Unified Data Platform Enables Accurate GPU Forecasting

Unified Data Platform for AI Capacity Planning Platform

A UK-based AI cloud provider partnered with Dataforest to transform fragmented operational data into a unified, Medallion-based analytics platform on Databricks. By integrating billing, infrastructure, CRM, and contract systems, the company gained trusted visibility into GPU/ASIC utilization and revenue performance. The new foundation enables accurate demand forecasting, confident capacity planning, and scalable growth for enterprise-grade AI infrastructure.

Internet & Technology

Data Engineering

Data Architecture Optimization

System Integrations Completed

100

Efficiency Improvement Achieved

Founded in 2020, this UK-based AI cloud provider is a global leader in sustainable AI infrastructure. Powered entirely by renewable energy, the company delivers GPU-accelerated compute environments designed for high-performance AI workloads while ensuring strict data sovereignty and compliance standards. Its portfolio includes a large-scale AI Supercloud for bespoke enterprise environments and an on-demand enterprise GPU platform that enables flexible capacity scaling. The company specializes in deploying and managing advanced AI infrastructure, helping organizations scale compute resources predictably, securely, and sustainably.

Databricks

AWS

Fivetran

PostgreSQL

Power BI

THE CHALLENGE

Fragmented Data Prevented Accurate Revenue, Utilization, and Capacity Forecasting

The client could not accurately understand or forecast the utilization of their GPU and ASIC capacity because their data was fragmented, low-quality, and stored across multiple unstructured sources. The company lacked the data-engineering foundation required to unify, clean, govern, and operationalize the data for predictive analytics. As a result, they could not reliably calculate revenue, utilization, occupancy, or model future demand.

Turn fragmented infrastructure data into actionable insights in 4 weeks.

THE SOLUTION

Designing a Medallion-Based Data Platform for Predictable GPU Utilization & Revenue Forecasting

We redesigned the client’s entire data foundation using a Medallion Architecture approach on Databricks, transforming fragmented operational data into a structured, governed, and analytics-ready platform.

‍

Instead of simply centralizing data, we engineered a layered architecture that progressively improves data quality, consistency, and business value — enabling reliable revenue modeling, utilization tracking, and capacity forecasting.

‍

We built a unified, analytics-ready data foundation that gives the client a clear understanding of their GPU/ASIC utilization, revenue, and capacity trends. The new architecture centralizes all operational data, ensures data quality, and provides a reliable SQL Warehouse for analysis, reporting, and future predictive modeling.

‍

Sub-Solution

1. Medallion Architecture Implementation (Bronze → Silver → Gold)

Implemented the Medallion Architecture to structure the client’s entire data landscape.

Bronze layer: ingestion and storage of all raw data from internal and external systems.
‍‍
Silver layer: cleaned, normalized, and analytics-ready datasets (occupancy, revenue, utilization). This provided a stable foundation for the client’s analysts to build dashboards and forecasting models.

3. Integrations with External Systems

Unified all compute-, billing-, and customer-related data sources into a single platform.
Integrated systems included:
‍

Billing & contracts
Gnokii VM data
HubSpot via Fivetran
NetBox
Remcode
Backup data sources for restoration

This integration allowed the client to finally see a full picture of how companies use their platform and how GPU/ASIC capacity translates into revenue.

2. Data Quality & Data Governance

Introduced end-to-end data quality checks and governance controls to address missing, inconsistent, and low-trust datasets.

Restored corrupted or unusable data from backups.
Standardized schemas and contract tracking logic.
‍
Implemented quality rules and validation steps before publishing to the SQL Warehouse. This ensured reliable business metrics and eliminated guesswork in their reporting.

THE RESULT

A Unified Data Foundation Helped Achieve Revenue & Capacity Visibility

The project transformed fragmented operational data into a strategic asset, giving leadership full visibility into GPU/ASIC utilization, revenue generation, and infrastructure occupancy.

By implementing a governed Medallion Architecture with integrated billing, infrastructure, CRM, and contract systems, the company gained a single source of truth for capacity, revenue, and demand signals.

‍

As a result, leadership now has:
‍

End-to-end visibility across 7 fully integrated operational systems
Reliable revenue-to-capacity correlation for pricing and planning decisions
Consistent occupancy and utilization metrics across the entire infrastructure
Elimination of manual reconciliation and reporting risks
Executive-ready dashboards powered by trusted, validated data
A scalable foundation to support AI-driven forecasting and future growth

The new platform enables confident capital allocation, accurate demand forecasting, and sustainable infrastructure expansion.

System Integrations Completed

100%

Efficiency Improvement Achieved

Unified Data Platform Enables Accurate GPU Forecasting

How we provide data integration solutions

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

At this stage, we need to ensure that we understand the full scope of the project. We receive from you or perform a set of interviews and prepare the following documents: integration pipeline (which data we should get and where to upload), process logic (how system should work); use cases and acceptance criteria; solution architecture. Ultimately we make a project plan which we strictly follow.

Step 3 of 5

Solution development

At this stage, we build ETL pipelines and necessary APIs to automate the process. We attract our DevOps team to build the most efficient and scalable solution. Ending up with unit tests and quality assurance tests to ensure that the solution is working properly. Focus on Results is one of our core values as well.

Step 4 of 5

Solution delivery

After quality assurance tests are completed, we deliver solutions to the client. Though we have over 15 years of expertise in data engineering, we are expecting client’s participation in the project. While developing the integration system, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

Success stories

All Success Stories

Medical Lab Achieves 50% Compute Savings via Databricks Migration

Sagis Diagnostics, a leading U.S. pathology lab, replaced its fragmented Azure SQL setup with a unified Databricks Lakehouse built by Dataforest. The migration consolidated 21 data sources, automated analytics, and ensured HIPAA compliance — delivering full data transparency, pay-per-use efficiency, and a ~50% reduction in compute costs.

~50%

compute cost reduction through optimized architecture

Integrated data sources unified under Medallion Architecture

View case study

Medical Lab Achieves 50% Compute Savings via Databricks Migration

Streamlined Data Analytics

We helped a digital marketing agency consolidate and analyze data from multiple sources to generate actionable insights for their clients. Our delivery used a combination of data warehousing, ETL tools, and APIs to streamline the data integration process. The result was an automated system that collects and stores data in a data lake and utilizes BI for easy visualization and daily updates, providing valuable data insights which support the client's business decisions.

1.5 mln

DB entries

integrated sources

View case study

Charlie White

Senior Software Developer Team Lead LaFleur Marketing, digital marketing agency

Their communication was great, and their ability to work within our time zone was very much appreciated.

Reporting Solution for the Financial Company

Dataforest created a valuable and convenient reporting solution for the financial company that successfully helped lower the manual daily operations, changed how access was shared, and maintained more than 200 reports.

solution to handle more than 200 reports

seconds to load a report

View case study