Data Warehousing & BI

Data Warehouse as the Foundation for Reliable Business Intelligence

We design and implement data warehouses on SQL Server and Azure Synapse Analytics. ETL/ELT pipelines, Star Schema following Kimball methodology and Power BI integration for consistent reporting across the whole organization.

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Single Source of Truth

Consolidation of ERP, CRM, manufacturing and finance data into one consistent store

Historical Data

Trends, seasonality and year-over-year analysis with a decade of data history

Analytics Performance

Optimized Star Schema and indexes for sub-second Power BI query response times

Data Quality

ETL/ELT pipeline with validations, deduplication and audit trail of every transformation

What is Data Warehousing and Business Intelligence?

A data warehouse (DWH) is a specialized analytical store designed for fast aggregation queries and historical analysis. Unlike transactional systems (OLTP), it is optimized for reading large data volumes across many dimensions.

We work with Kimball methodology – dimensional modeling with Fact and Dimension tables into Star or Snowflake Schema. Technologically we cover the full spectrum: SQL Server Integration Services (SSIS), Azure Data Factory, dbt (data build tool) for ELT transformations and Azure Synapse Analytics or Microsoft Fabric for cloud DWH.

Who is Data Warehousing For?

  • Mid-size and large companies with multiple source systems (ERP + CRM + manufacturing + finance)
  • Organizations suffering from report inconsistencies across departments
  • Companies needing historical analysis and trend reports over 5+ years
  • Controlling and finance teams requiring group data consolidation
  • Organizations transitioning from Excel reporting to Power BI needing a data foundation

Typical DWH Project and Timeline

Week 1–2
Data Discovery
Source system inventory, data catalogue, business requirements, KPI definition
Week 2–4
Dimensional Modeling
Star Schema design – Fact and Dimension tables, SCD (Slowly Changing Dimensions), granularity
Week 4–8
ETL/ELT Pipeline Development
Azure Data Factory / SSIS pipelines, staging layers, business transformations, data quality
Week 8–10
Semantic Layer & Power BI
Analysis Services / Power BI Dataset on DWH, DAX measures, row-level security
Week 10+
UAT & Go-live
Data validation against source systems, performance tuning, training, pipeline monitoring

Typical Data Warehouse Use Cases

Enterprise Financial Reporting

Consolidation of P&L, balance sheet and cash flow from multiple group entities into one DWH with automated Power BI reports for management.

Sales & Commercial Analytics

Integration of CRM, ERP and e-shop data – sales by customer, product, channel and territory with history and forecast.

Manufacturing & Operational DWH

OEE (Overall Equipment Effectiveness), production yield, planned vs. actual – MES and ERP data integration.

Migration from Excel Reporting

Replacing dozens of Excel reports with a consistent DWH, Star Schema, ETL pipeline and Power BI self-service analytics layer.

Free DWH Consultation

We map your data sources and propose data warehouse architecture. No commitment.

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Kimball certified architects
Azure Synapse & Fabric specialists
We respond within 24 hours
Related Services

FAQ – Data Warehousing & BI

A data warehouse is a central analytical store consolidating data from multiple operational systems. It enables consistent reporting, historical analysis and BI without loading production systems.

ETL transforms before loading – suitable for SQL Server. ELT loads raw data to the cloud and transforms in storage – cheaper and more flexible for Azure Synapse and Microsoft Fabric. We recommend ELT for new cloud projects.

Star Schema is a dimensional data model (Kimball methodology) with Fact and Dimension tables optimized for analytical queries. Power BI and SSAS are optimized for Star Schema – faster queries, more intuitive DAX.

SQL Server is suitable for DWH up to ~1 TB with fewer than 20 parallel users. Azure Synapse for petabyte-scale DWH with MPP and big data integration. For new projects we recommend Microsoft Fabric.

A basic DWH with 2–3 sources can be delivered in 8–12 weeks. An enterprise DWH with 10+ sources and a complex model takes 6–12 months.

Build a Reliable Foundation for Your Business Intelligence

Schedule a consultation and find out how a data warehouse eliminates inconsistent reports and enables strategic decisions based on data.

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