We design and implement pipelines, data lakes and data architectures that integrate all your sources into a reliable, scalable and AI-ready analytics layer.
These problems cost money every month and get more expensive the more they grow.
Data in silos — CRM, ERP, spreadsheets and third-party APIs that never talk to each other.
Handcrafted pipelines built on SQL scripts that break every time a table changes.
Reports that take hours to run because they query the production database directly.
Dirty, duplicated and inconsistently formatted data — each system with its own convention.
AI and machine learning are impossible because there is no reliable historical data foundation.
No governance: nobody knows who owns each piece of data, or what the official definition of a KPI is.
We implement Medallion architectures (Bronze → Silver → Gold) with ingestion from multiple sources via Azure Data Factory or Microsoft Fabric Pipelines, storage on Azure Data Lake Storage Gen2 and transformation with dbt or Databricks Notebooks.
The Gold layer feeds Power BI directly with data that is already modeled, cleansed and versioned. Every pipeline has orchestration, execution logs, failure alerts and technical documentation — nothing works as a black box.
A well-built data lake is not an infrastructure cost — it is the asset that multiplies the value of every analytics tool you already have.
A proven architecture that delivers value in short iterations — not a months-long big bang.
An inventory of all data sources, volumes, update frequency and priority analytics use cases.
Defining the architecture (Lakehouse, Data Warehouse or hybrid), choosing tools and the governance model.
Ingestion pipelines for the priority sources running with orchestration, logs and alerts configured.
Cleansing, enrichment and dimensional modeling for the analytics use cases defined in the discovery stage.
Connection to Power BI, documentation of the data catalog and training of the client data team.
Projects inspired by real market implementations.
Scenario
12 sources — ERP, CRM, marketplace, logistics API, cost spreadsheets — with no integration. The monthly report took 5 days and arrived inconsistent.
Solution
A Medallion data lake on Azure with automatic ingestion pipelines, a Gold layer modeled for Power BI and a full daily refresh in 1 hour.
Scenario
IoT sensors generated temperature, vibration and pressure data with no structured storage — lost data and expensive corrective maintenance.
Solution
A telemetry ingestion pipeline on Azure, a feature layer on Databricks and anomaly models integrated into the maintenance dashboard.
Scenario
Operations auditing required cross-referencing data from 4 distinct systems with no structured history — a process that took 3 weeks.
Solution
A data warehouse with incremental ingestion, lineage documented in Purview and an audit dashboard with drill-down by operation, date and owner.
We do not deliver quick pipelines. We design architectures that grow with volume and use cases — without a rewrite from scratch in 1 year.
Specialists in Microsoft’s unified platform — without fragmenting your environment into disconnected tools.
Data catalog, lineage and owner defined from the design phase — not as a retroactive documentation task.
First pipelines in production within weeks. We do not wait for the big bang — we deliver value in every sprint.
Book a free assessment. In 30 minutes we map your data sources and what can be built incrementally.