Data Integration · Data Engineering

Data Integration –
MICROSOFT FABRIC

This is the moment when it makes sense to build a data platform.

There comes a moment when a simple data structure is no longer enough. The number of sources and data volume grows, requests for more and more metrics keep coming, but the foundation, the data platform, isn't ready. How do we recognize it? Maintenance starts taking more time than actual work with data, changes are very demanding and often break the entire report.

Lakehouse Tables
sales_pipeline.ipynb Polars 1.x Run All
[1] Python 1.8s
# Load 3 sources into one model import polars as pl sales = pl.scan_delta("sales_data") outlook = pl.scan_delta("outlook_3m") plan = pl.scan_delta("year_plan") lf = sales.join(outlook, on="region")\ .join(plan, on="region")
[2] Python 0.3s
lf.select("region","sales","outlook","plan","status").collect()
Output
regionsalesoutlookplanstatus
CZ-Praha1 2401 3801 500✓ OK
CZ-Brno8709101 000✓ OK
SK-BA620580700⚠ Watch
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Lakehouse
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Cost-effective

We design a platform and solution that matches your needs and budget, without unnecessary oversized architecture.

Future-ready

Architecture that accounts for growth. When new sources or metrics are added, the platform scales without major rebuilds.

You can handle it yourself

A solution you can maintain and extend on your own. You don't need us for daily operation.

How does it work?


01

We start from a specific process

For example, reporting that combines existing sales data, a 3-month outlook, and an annual plan. Three different sources that need to be adjusted to fit together in one report.

02

We analyze and design

We analyze your process, understand its logic, and design a platform and solution that is cost-effective, future-ready, and that you can maintain and extend yourself.

03

We choose the technology

We choose technology based on your environment and needs. For example, the all-in-one Fabric solution, a combination of Azure services like Azure Data Factory and SQL Database, or the enterprise Databricks solution.

Microsoft Fabric
Technology

Microsoft Fabric

An all-in-one solution for a data platform. Everything under one roof, from ingestion to reporting, in the Microsoft 365 environment.

Azure Services

A combination of Azure Data Factory, SQL Database, and other services. A modular approach for teams that want full control over individual components.

Databricks

An enterprise solution for large data volumes and advanced analytics. For companies that need to scale and work with data at the data science level.

Guaranteed quality

Our expertise

1× Microsoft MVP
Microsoft MVP Fabric
8+ Years
Experience with Azure platform
4+ Years
Experience with Azure Databricks