Turn scattered data into a single source of truth. We build the modern, cloud-native data infrastructure you need to stop guessing, start deciding, and get ready for AI.
In business today, your biggest challenge isn’t collecting data—it’s using it. Scattered spreadsheets, slow reports, and disconnected systems mean you are making critical decisions based on guesses, not facts. Furthermore, this “messy data” is the single biggest bottleneck preventing you from adopting AI and Machine Learning.
Fifty One Degrees designs and implements scalable Data Warehouses and Business Intelligence (BI) systems that transform this challenge into your competitive advantage. We create a centralised, automated data foundation that enable:
Accurate, real-time reporting replaces manual spreadsheet crunching.
Your data is structured from day one to power Custom AI Models and Generative AI.
Automated, cloud-native pipelines reduce manual effort and eliminate human error.
We architect and deploy modern, cloud-native data platforms tailored to your business scale.
Cloud-Optimised Architecture: We utilise elastic resources (e.g., Snowflake, BigQuery) that scale costs with your usage, avoiding expensive upfront hardware.
Future-Proof Schemas: We design robust schemas (e.g., Star Schema, Data Vault) that make complex analysis simple and fast.
Legacy Modernisation: We seamlessly migrate data from older, on-premise systems to powerful cloud environments, ensuring no data is left behind.
Data Engineering is the heartbeat of your platform. We build reliable pipelines to deliver clean data where and when it’s needed.
ETL/ELT Automation: We build automated pipelines to extract, transform, and load data from your transactional systems (CRM, ERP, Marketing) into your central warehouse.
Transformation with dbt: We use dbt (data build tool) to apply rigorous business logic and testing within the warehouse. This ensures every report—whether for Finance or Sales—is built on the exact same definitions.
Real-Time Capabilities: For urgent needs like fraud detection or live inventory, we build streaming pipelines for instant data availability.
The final step is turning your data platform into an asset that empowers your team.
BI Tool Integration: We connect your warehouse to leading tools like Tableau and Power BI, creating intuitive, self-service dashboards.
Data Governance: We establish frameworks for metadata management and quality control, ensuring you remain compliant and secure.
We are cloud-agnostic advisors. We select the best technology stack for your specific infrastructure and goals.
GCP, AWS, Microsoft Azure
We deploy on the cloud environment that fits your existing IT ecosystem, ensuring security and ease of management.
Snowflake, BigQuery, Redshift
These “serverless” warehouses offer best-in-class performance and scale instantly without you needing to manage servers.
dbt, Fivetran, Airflow
Fivetran for reliable data extraction; dbt for transparent, version-controlled transformations; and Airflow for orchestrating complex workflows.
We analyse your data sources and business goals to design a roadmap that delivers quick wins. Deliverables include your Data Strategy Roadmap, Architecture Design, and Technology Selection (e.g., AWS vs GCP).
Timeline: ~4 weeks
We stand up your Data Warehouse and build the first critical pipelines to prove value immediately. Deliverables include your Secure Cloud Data Warehouse setup, ingestion of high-priority data sources (e.g., Sales/CRM data), and initial "Beta" dashboards for key stakeholders.
Timeline: ~12 weeks
Once the foundation is proven, we scale to include all data sources and advanced analytics. Deliverables include the full migration of remaining data sources, complex dbt transformations, comprehensive BI Dashboard suite, and training for your team.
Timeline: ~8 weeks
Direct connections work for small datasets, but they break as you scale. They slow down your operational systems (like your CRM) and often produce conflicting numbers because there is no central “source of truth.” Data Engineering builds a dedicated pipeline that cleans and centralizes data before it hits your dashboard, ensuring speed and accuracy.
A Data Warehouse stores structured, cleaned data ready for reporting and analysis—this is what most businesses need for day-to-day decisions. A Data Lake stores raw, messy data of all types. We often implement a hybrid approach (Modern Data Stack) that gives you the best of both: the structure of a warehouse with the flexibility of a lake for future AI use.
AI models are only as good as the data you feed them. If your data is messy, scattered, or undocumented, your AI projects will fail. A Data Warehouse provides the structured, high-quality data foundation required to train Custom AI Models and implement Generative AI successfully.
Yes. Major cloud providers (AWS, Azure, GCP) invest billions in security. We layer this with Enterprise-grade governance, encryption, and role-based access controls to ensure your data is often more secure than it would be on an on-premise server.
We aren’t just IT generalists; we are Data & AI Specialists. We build your data infrastructure specifically with the end-goal in mind: driving business value through Intelligence and AI. Our London-based team understands the UK mid-market and acts as your Fractional AI Officer to ensure long-term success.
Take three simple steps to start deploying AI in your business.
① Book an exploratory meeting
② Agree a proposal
③ Design & build your AI implementation
The AI-First Playbook: How to Get Your Entire Team Using AI | Fifty One Degrees
Half of UK SMEs now say they’re likely to replace some staff roles with AI.
Fifty One Degrees offers Data Engineering and Business Intelligence services to build scalable, cloud-native data infrastructure. Their solutions focus on creating a single source of truth from scattered data to enable faster decision-making, AI readiness, and operational efficiency. The service includes data warehousing, automated data pipelines (ETL/ELT), and BI tool integration, with a phased implementation process.
Direct connections work for small datasets, but they break as you scale. They slow down your operational systems (like your CRM) and often produce conflicting numbers because there is no central “source of truth.” Data Engineering builds a dedicated pipeline that cleans and centralizes data before it hits your dashboard, ensuring speed and accuracy.
A Data Warehouse stores structured, cleaned data ready for reporting and analysis—this is what most businesses need for day-to-day decisions. A Data Lake stores raw, messy data of all types. We often implement a hybrid approach (Modern Data Stack) that gives you the best of both: the structure of a warehouse with the flexibility of a lake for future AI use.
AI models are only as good as the data you feed them. If your data is messy, scattered, or undocumented, your AI projects will fail. A Data Warehouse provides the structured, high-quality data foundation required to train Custom AI Models and implement Generative AI successfully.
Yes. Major cloud providers (AWS, Azure, GCP) invest billions in security. We layer this with Enterprise-grade governance, encryption, and role-based access controls to ensure your data is often more secure than it would be on an on-premise server.
We aren’t just IT generalists; we are Data & AI Specialists. We build your data infrastructure specifically with the end-goal in mind: driving business value through Intelligence and AI. Our London-based team understands the UK mid-market and acts as your Fractional AI Officer to ensure long-term success.
