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, Cubis 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 Cubis approach
Rely on us to engineer analytics-ready data directly within SAP landscapes and modernize BW estates without business disruption.
- Ingest and replicate SAP data via ODP extractors, SLT/CDC, CDS Views, and Open ODS: reliable deltas, minimal load on source.
- Model in BW/4HANA (ADSOs, CompositeProviders, Process Chains) with robust scheduling, monitoring, and error handling.
- Accelerate Datasphere adoption: space design, Replication Flows/Data Flows, semantic modeling, and federation back to SAP.
- Hybrid architectures that combine BW/4HANA & Datasphere, keeping critical logic close to SAP while opening up cloud scale.
- Governance and transports aligned with SAP standards (lifecycle, authorization, lineage), plus SAC integration for consumption.
- BW modernization and migration roadmaps: carve-out of legacy flows, performance tuning, and phased migration to Datasphere.
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.
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