Data warehouse tailored to your company’s needs
We started with CRM, but today we increasingly help companies organize their entire flow of information: from sales and customer service systems, through integrations, all the way to data warehousing, reporting and decision automation. We don’t push a single technology. We choose the solution that fits your scale, budget, data sources and real business questions.
CRM, ERP, e-commerce, forms, files, API
one organized information model
dashboards, KPIs, automations, AI
When does a company need a data warehouse?
Most often when data lives in many systems, reports are built manually, and management and sales see different versions of the same truth.
Reports are manual
The team exports data to Excel, fixes it by hand, and spends time preparing reports instead of making decisions.
Data is scattered
CRM, ERP, the store, marketing, customer service and finance all run separately, making it hard to see the full picture of a customer or a result.
There’s no single source of truth
Different departments calculate KPIs differently. A data warehouse organizes definitions, sources and ownership of data.
We tailor possible solutions to your needs
Not every company needs a large data platform right away. Sometimes a well-designed reporting model is enough, sometimes a cloud data warehouse, and sometimes a hybrid or phased solution.
Lightweight reporting model
For companies that want to quickly organize KPIs, recurring reports and basic data sources without building a complex architecture.
Cloud data warehouse
For organizations that need a place for their data that grows with volume, automated data loads, an analytical model and stable reporting.
Hybrid architecture
For companies with security requirements, older on-premise systems, or a need to combine on-premise data with cloud services.
How we work on your data warehouse
01
Business questions
We determine which decisions need to be made based on data and which KPIs are actually needed.
02
Data sources and quality
We map your systems, check data quality, field definitions, API availability and data ownership.
03
Model and reporting
We build the data model, automated data loads, dashboards and maintenance rules so that reporting stays repeatable.
Data warehouse vs reports in Excel
Excel is good for ad hoc analysis, but it shouldn’t be your main management reporting system. A data warehouse automates data loading, standardizes KPI definitions, and reduces manual fixes in reports.
Less manual work
Data flows into reports automatically, without copying files, manual exports or fixing spreadsheets.
One set of KPI definitions
Sales, finance and management all work from the same definitions of margin, revenue, pipeline and sales activity.
Stable dashboards
Power BI, Looker or Tableau run on an organized data model instead of manually updated files.
Example uses of a data warehouse
- management reporting and a single source of truth
- sales, marketing and customer service dashboards
- data integration from CRM, ERP and e-commerce
- automatic KPIs and recurring reports
- preparing data for AI and decision automation
- monitoring data quality and definition consistency
If the problem starts with your CRM, also check out our CRM cost audit. If you want to reduce license costs and vendor lock-in, see our open source for companies. If you’re looking for a CRM platform with automation, also check out Creatio. You’ll find project examples in the case studies.
Frequently asked questions about data warehouses
What is a data warehouse?
A data warehouse is an organized place where a company brings together data from multiple systems, such as CRM, ERP, e-commerce, forms, files and APIs. This lets reports run on a single information model.
When is it worth implementing a data warehouse?
It’s worth implementing when reports are built manually, data is scattered, KPIs differ between departments, or management needs stable dashboards for decision-making.
Does a data warehouse replace CRM or ERP?
No. A data warehouse doesn’t replace CRM or ERP. It combines data from these systems and organizes it for reporting, analytics, automation and data quality control.
How much does implementing a data warehouse cost?
The cost depends on the number of data sources, data quality, the scope of reports, the chosen technology and the maintenance model. Projects usually start with an analysis of sources, KPIs and priority reports.
Does a data warehouse help with Power BI reporting?
Yes. Power BI runs more reliably when it uses an organized data model instead of many manually updated files. A data warehouse improves report repeatability and dashboard quality.
Want to talk? Get in touch.
