Data Warehousing
Data warehouses, ETL/ELT pipeline and business intelligence.
What is Data Warehousing?
A data warehouse is a centralized repository of data from various sources, optimized for analytical queries and reporting. We implement data warehouses on Microsoft technologies – Azure Synapse Analytics, Microsoft Fabric or classic SQL Server.
Implementation includes a complete ETL/ELT pipeline for extracting, transforming and loading data, a dimensional data model (Star/Snowflake schema) and a layer for BI tools like Power BI.
Who is this solution for?
- Companies with data scattered across different systems (ERP, CRM, Excel)
- Organizations looking for a single source of truth for reporting
- Companies preparing for advanced analytics and AI
- Businesses with high volumes of transactional data
Typical use cases
ETL/ELT pipeline
Automatic data loading from ERP, CRM and other sources
Dimensional modeling
Star schema for optimal BI query performance
BI reporting layer
Semantic model for Power BI
Predictive analytics
Foundation for machine learning and AI models
How does collaboration work?
1
Data audit & architecture
Analysis of source systems, DW architecture design.
2
ETL development
Implementation of data extraction and transformation pipelines.
3
Data model
Design and implementation of dimensional model.
4
BI layer & testing
Semantic model, data validation, performance tuning.
FAQ
A data warehouse is suitable if you have multiple data sources, need history, data transformation or performance for large volumes. For simple reports from one source, direct connection is sufficient.
Depends on number of source systems and complexity. Typically 2–6 months. First data and reports can be available in 4–6 weeks.
Azure Synapse or SQL Server in Azure typically costs $150–700/month depending on data volume and queries. We help optimize costs.
Ready to take your processes to the next level?
Schedule a free consultation. We will evaluate your automation and digitalization potential at no cost.