Data Engineering
Data engineering: structure your data to drive and automate your business.
PULSE.digital designs and implements reliable data architectures: pipelines, data warehouses, data lakes, analytical models and data APIs. We help your teams collect, transform and expose data properly to power your digital products, reporting and AI use cases.
- IT-first approach: security, scalability and operations from day one
- Integrated data quality: tests, traceability, error handling
- Clear and documented architecture, easy to maintain
They structured their data with us
Our data clients
When data is everywhere, but not usable.
Data engineering becomes critical when your performance depends on data from multiple sources, with needs for reliability, traceability and regular updates.
Data scattered across ERP, CRM, business tools, SaaS and files
Reporting slow to produce, unreliable or too dependent on a few people
Need for near real-time indicators to drive business
Digital products or automations requiring clean and available data
Growing volume requiring industrialization and governance
In these situations, a well-architected data chain brings clarity, confidence and operational acceleration.
What we build, concretely.
Pipelines and data integration
Multi-source collection, ETL/ELT, batch or real-time synchronization, quality and monitoring.
Data warehouse / lakehouse
Modeling, normalization, historization, governance and query performance.
Data exposure and consumption
Data APIs, BI dashboards, data products for business teams or SaaS products.
An approach focused on reliability and business uses.
Data scoping + objectives
Sources, business needs, indicators, freshness levels, security/compliance constraints.
Architecture and modeling
Platform choice (DWH, lakehouse), schemas, flows, governance and standards.
Implementation + quality testing
Pipelines, transformations, data tests, documentation, CI/CD data automation.
Production + operations
Monitoring, alerts, cost/performance optimization, data evolution roadmap.
Why PULSE.digital.
We build a data chain designed to last: robust, auditable and aligned with your business priorities.
IT-first approach: security, scalability and operations planned from the start
Swiss governance and senior teams in Morocco
Integrated data quality: tests, traceability, error handling
Clear and documented architecture, easy to take over by your teams
Clean connections to your IS (ERP, CRM, SaaS, APIs)
Rapid data availability for BI, products and AI
Frequently asked questions
Data engineering vs BI, what's the difference?+
Data engineering builds the foundation (collection, transformations, models). BI consumes this foundation to produce dashboards and analyses.
How much does a data architecture cost?+
The budget depends on the number of sources, volume, real-time level and uses. We give a first range after scoping.
Can we start small?+
Yes. We generally target a priority scope (1-2 sources + some KPIs), then expand gradually.
Do you work with our existing stack?+
Yes. We adapt to your environment (cloud, DWH, ETL/ELT tools, BI) and suggest adjustments if needed.
Do you handle operations and optimization?+
Yes. Monitoring, alerts, performance and cost optimization, evolutions via a shared data roadmap.
Let's talk about your data chain.
Whether you need to centralize your data, make your indicators more reliable, or feed digital products and AI use cases, we scope your needs and deliver a robust, clear and scalable data architecture.
Whether you need to centralize your data, make your indicators more reliable, or feed digital products and AI use cases, we scope your needs and deliver a robust, clear and scalable data architecture.