Data Engineering and Platforms
Despite holding more data than ever, enterprises remain frustrated by incomplete information, blocked analytics teams, and time lost to Excel consolidation. We help enterprises by designing and building modern, scalable data platforms. Our approach is hands-on, from data modelling that creates structured views your stakeholders can act on, to data integration that brings fragmented sources together into a unified, reliable foundation.
Our Work
Ninety One’s embarked on a strategic data transformation initiative to modernise how data is accessed, governed, and shared across the organisation.
The team needed to improve accessibility to trusted data across internal and external stakeholders while aligning with enterprise-wide governance standards.
The project would require integrating multiple systems, supporting secure data sharing, and enabling consistent, consumable datasets for analytics and reporting.
We implemented a cloud-native architecture using Azure Databricks, with data layers to standardise data ingestion, transformation, and consumption.
The platform provides scalable ETL, analytics, AI, and dashboarding capabilities, with flexible deployment pipelines and secure data connectivity across the the department.
Improved access to trusted data: Teams can securely access aggregated, queryable datasets for self-service analytics and decision-making.
Streamlined data sharing: Automated and secure delivery mechanisms simplify collaboration across internal and external stakeholders.
What We Do
Data Modelling
We create structured views of your data – enabling both human understanding and machine-driven insights. Our models are designed to support analytics, reporting, and advanced AI use cases such as feature engineering and predictive modelling.
Data Integration
Entelect brings together fragmented and disparate data sources into a unified foundation – ensuring data is AI-ready, consistently structured, and accessible for both operational intelligence and machine learning pipelines.
Data Quality and Governance
Our engineers embed validation, lineage tracking, and governance frameworks across your platform – ensuring data is accurate, explainable, and compliant.
Real-Time Data Processing
We build systems that ingest and process streaming data as it happens – enabling real-time analytics, event-driven architectures, and AI use cases such as anomaly detection, recommendation engines, and automated decisioning.
Scalability and Performance
The platforms we engineer are made to grow – handling increasing data volumes without sacrificing speed, reliability, or operational continuity.
Data Assets and Pipelines
We build pipelines that transform raw data into reusable data products – supporting dashboards, analytics, and AI use cases including model training, feature stores, and inference pipelines.
AI-Ready Data Foundations
We design data platforms specifically for AI readiness –structured to support model development, feature engineering, and scalable AI deployment.
As a Databricks implementation partner, Entelect combines deep platform expertise with an outstanding track record. Our close partnership and their consistently excellent project execution makes them a trusted choice
Guillaume Meister
Databricks EMEA Field, Engineering Manager
KEY PARTNERS
