Databases that stay fast, protected and understood by more than one person.
I help businesses whose operations depend on a database that nobody has examined recently, by tuning it, securing it and documenting how it works.
Where the problem shows up
Almost every business system depends on a database, and a database that responds today is usually left alone. Reports run, records save and integrations work, so attention goes to the applications on top, which are the part that users can see.
The difficulty is that database problems stay invisible until they become serious. Queries slow down a little each month as data grows, schema decisions made early create constraints later, and backup procedures that were never tested fail at the moment they are needed. When the one person who understands the structure leaves, the knowledge leaves too. What happens to financial reports, customer records and automations when the database underneath them fails or slows beyond use? And how long would recovery take if nobody has ever practised it?
The better principle is to treat the database as a representation of how the business understands its own operations, and to keep that representation accurate, tested and documented. That is the work I do.
What I have changed for others
Market research data: one PostgreSQL environment for 6.4 million records
A research setup relied on separate files that were prepared again for each experiment. I designed a PostgreSQL architecture with indexing for repeated analytical queries, 21 native timeframes kept as recorded, and raw data separated from derived outputs, avoiding heavy normalisation and partitioning until scale justified them. The database now holds more than 6.4 million historical price records, with more than 1.3 million observations for a single instrument. Read the case study.
HIPAA-regulated platform: recovery and documentation built in
A nationwide platform needed a database environment that was secure, auditable and recoverable. I led the platform end to end and built role-based access control, audit logging, Redis, disaster recovery and production documentation with developer onboarding. The platform runs with page loads under 2 seconds and a 100% uptime SLA. Read the case study.
60+ websites: a warehouse with a shared schema
Analytics data from more than 60 websites was stored differently on each one. I designed the schema and centralised the data in a BigQuery warehouse, so results can be compared across properties. Read the case study.
What changes for your business
Queries stay fast as data grows, backups are restored in practice and not only on paper, and access to sensitive data is controlled and auditable. The structure is documented, so the business no longer depends on one person. The work can include performance analysis and query optimisation, schema review and design, backup and recovery planning with tested restoration, security configuration and monitoring, and architecture documentation.
Where this leads next
A healthy database is the base of information systems, and it makes infrastructure recovery realistic. If your database is already tested and documented, we can begin with reporting or integration.