Microsoft Fabric

Overview

Microsoft Fabric is an end-to-end analytics platform unifying data engineering, data integration, data science, business intelligence and governance under a single, SaaS-based architecture. Built on OneLake, a multi-cloud, lake-first storage system, Fabric streamlines how enterprises ingest, transform, model and analyse data at scale.

Fabric consolidates multiple analytics workloads into one unified platform, replacing the need for multiple siloed tools. It integrates seamlessly with Power BI, Azure services, and enterprise governance frameworks, making it a powerful choice for organisations seeking a modern, centrally managed analytics ecosystem.

What we do

At High Digital, we use Microsoft Fabric to build modern, scalable and governed data platforms for clients across multiple sectors. Our expertise includes:

Designing Fabric-based data architectures
Building ingestion pipelines with Data Factory
Developing scalable transformations in Data Engineering (Lakehouse)
Creating enterprise data models in Power BI and Semantic Models
Integrating Fabric with external warehouses, APIs and operational systems
Implementing governance, lineage and security across Fabric workloads
Building AI-ready datasets for automated insights and agentic workflows

We specialise in modernising analytics platforms, reducing tooling complexity and delivering end-to-end value through Fabric’s unified environment.

Why We Use Microsoft Fabric

Unified End-to-End Platform

Fabric merges ingestion, transformation, storage, modelling and visualisation within one ecosystem — significantly reducing technical complexity.

OneLake for Centralised Storage

A single multi-cloud lake underpinning all Fabric workloads eliminates duplication and enables shared datasets across teams.

Native Power BI Integration

Fabric offers the most seamless BI pipeline available: ingestion → model → visual → share — all without switching platforms.

Enterprise Governance & Lineage

Built-in governance tools, security controls and lineage tracking ensure analytics remain auditable, compliant and trustworthy.

Flexible and Scalable

Fabric workloads automatically scale with demand, supporting both small reporting environments and large enterprise data warehouses.

Ideal Foundation for AI

Fabric’s unified semantic layer and centralised modelling enable reliable foundations for AI automation, predictive analysis and agentic AI systems.

Use Cases at High Digital

Enterprise Data Warehouse Modernisation

Fabric’s OneLake architecture provides a unified storage and compute environment for centralised, governed enterprise analytics.

Operational Dashboards and KPI Reporting

Using Power BI, Data Factory and semantic models, we create reliable reporting systems with automated refresh, security controls and high scalability.

Hybrid Analytics with ClickHouse

Fabric handles ingestion, modelling and governance while ClickHouse provides sub-second analytical performance, giving clients a hybrid architecture that excels across different workloads.

AI-Ready Data Foundations

Fabric works seamlessly with ML and agentic AI workflows by providing high-quality, centrally managed data models and real-time ingestion paths.

Data Integration Across Legacy Systems

With connectors for ERP, CRM, MES, IoT and external APIs, Fabric acts as an enterprise fabric layer for consolidating fragmented data sources.

Why We Use Tailwind CSS

Tailwind CSS gives us full control over the design system while speeding up development. Its modular approach ensures that designs are both consistent and easy to maintain.

Technologies we use

Frontend

React.js

Next.js

Tailwind CSS

Angular.js

Backend

Python

Fast API

.Net

Node.js

Databases

MS SQL

PostgreSQL

MongoDB

Databricks

Cloud & DevOps

Microsoft Azure

AWS

Google Cloud

GitHub Actions

Key Fabric Technologies

OneLake (central lake-first storage for all Fabric workloads)

Data Activator (rule-based triggers for event-driven actions)

Data Factory (pipelines, dataflows, ingestion and orchestration)

Data Science (ML notebooks, model training, integration with Azure ML)

Data Engineering / Lakehouse (Spark, Delta Lake, notebook and pipeline execution)

Real-Time Analytics (KQL databases, event processing, streaming insights)

Power BI (semantic models, reports, dashboards and distribution)

Governance & Purview Integration (catalog, lineage, RBAC and compliance controls)

Why We Use Tailwind CSS

Proven track record delivering high-impact digital products

Deep technical expertise across modern stacks

Focus on data, scalability, and user experience

Collaborative and client-first mindset

Looking to build a modern data platform or enhance your analytics capabilities?

Let’s Talk

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