Reconcile sales across three systems
The till, the online shop and the ERP record the same sales with different identifiers.
Design and development of your data architecture: reliable systems, optimized data flows, migration and Snowflake or BigQuery warehouses.
- Connect applications, databases and exports
- Structure data in a data warehouse
- Make data pipelines reliable and documented
Concrete use cases.
Make a failing pipeline reliable
A daily export sometimes fails silently and distorts the morning indicators.
How can we bring our data together without adding manual processes?Appointments
Connect sources to a common model
An ERP, a CRM and spreadsheets often describe the same activity using different identifiers and rules. Data engineering organizes collection, transformation and storage, including on Snowflake or BigQuery, so these sources can be used together. We start with the available sources, their quality and the refresh frequency the business actually needs.
Pipelines your team can maintain
The project covers transformation rules, quality checks and error handling. Batch processing or more frequent updates are selected according to business needs, API limits and budget. Documentation and handover help your teams understand the system instead of depending on opaque processes.
Frequently asked questions
Do we need to replace our existing applications?
Not necessarily. We use available interfaces such as APIs, exports and authorized database access. An initial assessment identifies possible connections, required permissions and limitations of your applications.
What should we prepare before starting?
A list of sources, a sample export, the expected indicators and access to people who understand the data are a useful starting point. Technical access and security rules are defined during scoping.