Data modelling and warehousing for startups and operations teams
I help teams redesign schemas, warehouse structures and reporting models when growth, new data sources or operational pressure expose the limits of the current setup.
- Schemas that no longer fit current reporting
- Data flows that break as volume grows
- Warehouse structure people can work with
- Safer schema changes and staged migrations
Data structures that make reporting easier to work with
Schema cleanup and redesign
Restructure existing databases to reduce redundancy, improve query performance and support changing business requirements without breaking working processes.
Dimensional modelling
Design star and snowflake schemas with clear fact and dimension tables that make reporting fast, intuitive, and maintainable.
Data vault where it fits
Implement hub, satellite and link structures in environments that genuinely need traceability, multiple source integration and room for change.
ETL design
Design and improve data movement pipelines using SSIS, stored procedures or newer tooling, with a focus on reliability and clarity.
Warehouse performance
Improve warehouse performance with better partitioning, indexing, incremental loads and aggregation where it actually helps.
Data quality & governance
Implement validation rules, deduplication logic, and data lineage tracking to ensure the warehouse delivers trustworthy data.
Design for the questions you need to answer
Good data modelling starts with understanding what people need to answer, not with theory for its own sake. I work backwards from reporting and analytics needs to shape schemas that answer real questions efficiently and still leave room to evolve.
- Requirements-driven design, not theory for theory's sake.
- Schema validation against actual query workloads.
- Migration strategy that runs alongside the existing system.
- Documentation your team can maintain long term.
Common questions about data modelling
How do I know if my schema needs a redesign?
Common signs include queries that require too many joins, reports that stay slow despite indexing, duplicated data across tables and difficulty adding new data sources. If the structure keeps getting in the way of reporting or ETL, it is time to review it.
Star schema or data vault: which should I use?
It depends on your needs. Star schemas are simpler and ideal for reporting-focused warehouses. Data vault is better when you need full auditability, handle many source systems, or expect frequent schema changes. I help you choose based on your actual requirements.
Can you migrate data to a new schema without downtime?
Yes, with planning. I design migration strategies that run in parallel, populating the new schema while the old one remains active, and cut over once validation is complete. The goal is zero or minimal disruption.
How long does a warehouse redesign typically take?
It varies widely based on scope. A focused schema redesign for a single subject area might take 2–4 weeks. A full warehouse build or major restructure is a longer engagement. I scope it after reviewing your current state and goals.
Ready to fix your data architecture?
Describe your current situation, what's not working, and what you need. I'll review it and outline what a better structure looks like.
