Data Engineering & Modelling

Build a data foundation you can trust

To get fast, consistent, and reliable insights in your operations, you need a solid data engineering setup. We can help you build data platforms that make data available, usable, and scalable. No more broken reports, just decisions that stick.

What is Data Engineering & Modelling?

Data engineering means turning raw, scattered data into structured, reliable inputs for analytics, reporting, machine learning, and operational use.

It includes the design, construction, and maintenance of pipelines, workflows, and processing systems that move and transform data accurately and smoothly.

So are you ready to turn raw data into business value?

As part of Intellus Group, Lytix helps organizations build modern data platforms that support both real-time and large-scale batch processing. Our solutions are built to:

Ingest, clean, and transform structured and unstructured data
Handle high-throughput, incremental data processing
Scale to match future data volumes and complexity
Deliver analytics-ready datasets that are consistent and trusted across the organization

With the right systems and expertise, your organization can move from data chaos to data clarity and translate insight into impact.

Why does it matter to you?

As data grows in volume, variety, and speed, it becomes harder to manage and trust. Without strong data engineering, you’re bound to end up with conflicting reports, repeated manual work, or disconnected systems. A well-built data model lets you ask questions and get consistent answers, fast.

These five areas are key:

Data Quality & Reliability

Clean, consistent, and validated data pipelines reduce errors and build confidence in what you’re seeing.

Automation & Efficiency

Manual work is replaced with automated workflows. The payoff? Faster delivery, less human effort.

Incremental & full processing

Both ongoing updates and full data loads are supported, depending on the source and business need.

Scalable Architecture

Adding users, workloads, or entirely new use cases? Our designs scale horizontally, so you can grow without slowing down.

Ease of use & Uniformity

A clear, structured data model avoids duplication and makes sure business logic is applied consistently. The result? Everyone uses the same definitions and numbers, reporting is efficient, and there’s only one version of the truth.

Want to turn data from a technical burden to a strategic asset? Our 130+ dedicated consultants are here to help.

How we make it work for you

Data engineering is the operational backbone of a modern data-driven company. That’s why we don’t just build pipelines. Together, we’ll create a stable, sustainable foundation for all your data operations.

Discover & Define

Let’s start with your existing data sources, business goals, and success metrics – and define together what your future platform needs to support.

Architect & Build

Resilient, scalable pipelines are designed and developed, tailored to your architecture: cloud, hybrid, or on-prem.

Automate & Optimize

We implement orchestration, automation, and monitoring to reduce cut manual effort and maintain speed, reliability, and performance as your platform grows.

Operationalize & Evolve

Expect production-ready solutions that grow along with your needs. Supporting analytics, reporting, AI, and more? Check!

Support

Support doesn’t end after delivery. Count on our expert team to stay involved to keep systems healthy, aligned with evolving needs, and up to date with new tools or features on the market.

Get to know the Lytix approach

Rely on us to build fast, governed data platforms on Microsoft, from Synapse foundations to Fabric’s unified Lakehouse.

Fabric Lakehouse & Warehouse on OneLake using a medallion layout (bronze/silver/gold) for clean, reusable data products.

Pipelines & Dataflows Gen2 for ingestion and transformation and Notebooks (Spark/SQL) for scalable processing.

Synapse best practices: Serverless/Dedicated SQL, Spark, and integrated orchestration for batch/near-real-time workloads.

DataOps/CI-CD with Azure DevOps & Git integration (environments, approvals, automated tests, artifact promotion).

Security and governance using Entra ID and Microsoft Purview (catalog, lineage, policies) across Fabric/Synapse assets.

Power BI semantic models optimized for performance and self-service; clear migration paths from Synapse to Fabric.

Need help with Data Engineering and Modelling?

Are you just getting started with big data or do you need support to improve your current setup? Let us help you get more value from your data.

We work with you to:

Identify the right architecture for your business and use case
Implement and configure the chosen technologies
Set up services and connections across your data environment
Write the necessary code to transform raw data into useful, trusted output

You’re in the right place if you’re looking for a partner who combines technical expertise with hands-on delivery. Want to make sure your data systems don’t just exist, but actually work for you? We’ll make it happen, together.

Let's talk

Trusted by

"It wasn't until Cubis structured our data that we knew what a huge potential we had."

Manuel Correia

Director Business Intelligence, Cargolux

“Lytix helped us setting up a robust Power BI environment in terms of user adoption, governance, training & support.”

Steven Dauw

Infrabel Teamlead End User Products & Reporting

“Lytix ensures that we stay within our SLA and that we have a great customer experience! They are driven to increase our maturity & to support the related change management.”

Maurijn Van Malderghem

Infrabel BI ICT Lead

“Businesses and industry groups traditionally relied on reporting systems that were complex to manage. Increasingly, business wants the ability to quickly answer complex analytical questions without the involvement of IT”.

Stijn De Knop

CDP/CFO at Torfs

"Carglass has chosen Lytix & Microsoft Power BI to modernize their front-end reporting strategy. Bringing great additional value with modern looking dashboards and easy-to-use user interface."

Johan Van Hentenrijk & Inge Vossen

Business Controller EDC & Business Finance Manager

Insights

Explore the latest insights on Data Engineering & Modelling

One User. Two Clicks. 553,000 Compute Units.

How to keep your Microsoft Fabric capacity under control Introduction Microsoft Fabric promises a unified analytics platform, one capacity, one bill, everything in one place. But that simplicity comes with a catch: every workload on your capacity competes for the...

Building a Databricks Environment on Azure: A step-by-step practical guide

1. Why Databricks On Azure Databricks has become the go-to data platform for a lot of companies of different sizes and different industries. The evolution from a managed-Spark platform to a fully fledged platform with Governance, AI, ML, BI solutions...

Download whitepaper

Databricks GenAI Bootcamp

October 8, 2026 08:30

Get hands-on with the Data Intelligence Platform The Databricks Getting Started with GenAI bootcamp will introduce you to the Databricks vision on GenAI applications and the Data Intelligence Platform. It will cover GenAI fundamentals, as well as basics of the Databricks...

Subscribe here

Materialized Lake Views in Microsoft Fabric: your medallion pipeline in a few lines of SQL

Data engineering on a lakehouse used to mean a lot of moving parts. A notebook for each transformation layer. A Data Factory pipeline to run them in the right order. Custom validation logic across scripts. Schedules to maintain and a...

Top insights from the Databricks Data + AI Summit 2026

Every year in June, the focus of the Data & AI world switches to San Francisco, where Databricks holds its yearly Data & AI Summit. A packed three days full of new product announcements, customer success stories and interesting talks....

Databricks on AWS – Accelerating scalable data platforms through the Intellus metadata-driven framework

1. Introduction Organizations today are operating in an environment where data has become both a strategic asset and an operational challenge. Volumes are increasing rapidly, sources are more diverse than ever, and expectations around speed, quality, and accessibility continue to...

Download whitepaper