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Data & AI

Robust Data Engineering

Build the foundation for your business intelligence. Reliable, scalable, and secure data pipelines.

Modernize Data

Quality Data, Quality Decisions

Before any AI or Analytics project, you need clean, organized, and accessible data. Data engineering is the invisible foundation of any data-driven company.

At Avantit, we specialize in building modern data architectures (Modern Data Stack) using the best tools in the Azure ecosystem, such as Data Factory, Databricks, and Synapse.

  • Medallion Architecture (Bronze, Silver, Gold)
  • Complex workflow orchestration
  • Monitoring and failure alerts
  • GDPR compliance
Azure Synapse Analytics and data engineering by AvantIT — ETL pipelines, data warehouse and data lake architecture

Engineering Services

ETL/ELT Pipelines

Development of automated data flows to extract, transform, and load data from multiple sources.

Data Lakes & Warehouses

Scalable storage architecture (Lakehouse) for structured and unstructured data.

Real-time Processing

Ingestion and processing of data streams for immediate insights (Spark Streaming, Event Hubs).

Data Governance

Implementation of data catalogs, lineage, and quality policies to ensure trust in information.

Typical Projects

Customer 360 View

Customer 360 View

Unification of data from CRM, ERP, website, and social media to create a single customer profile.

Cloud Migration

Cloud Migration

Modernization of on-premise databases to Azure SQL or Synapse Analytics.

IoT Analytics

IoT Analytics

Collection and processing of industrial sensor data for predictive maintenance.

Are your data scattered?

Let's centralize and organize your information.

Talk to a Data Engineer

Frequently Asked Questions

Frequently Asked Questions

Get answers about this service

A dependable path from the systems that hold your data to the place decisions are made from — ingestion, cleaning, joining, and a schedule that runs whether anyone remembers it or not. The visible outcome is that a report is right on Monday morning without someone spending Friday assembling it.
Power BI alone is enough while one team reports on a handful of sources and the definitions live in one person's head. You need something behind it once two departments disagree about what 'revenue' means, once refreshes start timing out, or once the same transformation is copy-pasted into several reports. That is the point at which the logic belongs in one modelled layer rather than in every report.
A SQL database is the right answer more often than vendors admit, and it is the cheapest to run and to hire for. Microsoft Fabric is worth it when you want storage, transformation and Power BI under one capacity and one governance model. Synapse remains reasonable for existing estates already built on it. We would rather size this to your data than to the roadmap.
Database replicas, scheduled exports, or an on-premises data gateway for systems that cannot be reached from the cloud. Older ERP and accounting systems are common in Portuguese SMEs and are rarely a blocker — the constraint is usually the licence terms of the system, not the technology.
Whoever you want to. Pipelines are delivered as code in your own repository with the deployment steps documented, so they can be read, reviewed and changed without us. We would rather hand over something maintainable than keep a dependency.