Data and analytics
Data platforms and management and regulatory reporting in which every metric has a single definition.
Overview
We build data platforms that collect information from company systems in one place, along with reporting for management and operations teams. Every metric has a single definition, an owner and a description of how it is calculated.
We design reports starting from the decision they are meant to support. For each user group we agree on a few of the most important metrics and the thresholds at which the system sends a notification.
We also prepare the data platform for future AI use, with data quality checks, change history and permissions.
Scope of work
- Data platform architecture
- Data pipelines with quality tests
- Metric dictionary with definitions
- Reports and dashboards for departments
- Notifications when thresholds are exceeded
- Permissions and documentation
Project flow
- 01
Source review
We document the source systems, data volumes and existing reports. We establish which metrics differ today and why.
- 02
Architecture
We match the solution to the scale and budget, from a PostgreSQL database to a cloud data warehouse or lakehouse.
- 03
First area
We launch the data pipeline and reports for one department. At this stage we verify data quality and metric definitions.
- 04
Expansion
We add further sources and areas in the agreed order, with quality tests and documentation.
When it makes sense
- The same metric has different values depending on the department that calculates it.
- Management reports are compiled by hand from several systems.
- Data is needed for an AI project, but its quality is unknown.
- Current reports are rarely used and do not support day-to-day decisions.
Technologies
Technologies are selected to suit the project and the client's environment. The ones we most often work with:
- PostgreSQL
- dbt
- Apache Iceberg
- Databricks
- Snowflake
- BigQuery
- Power BI
- Metabase
Frequently asked questions
Not always. At a smaller scale a well-designed PostgreSQL database is enough. We prepare a recommendation after the source review.