About SchemaHelm
What SchemaHelm does
SchemaHelm helps businesses understand why reports, spreadsheets, databases and business systems do not always agree.
The work focuses on tracing where data comes from, how it moves, where it changes and why different outputs may be showing different answers.
Current core capabilities include SQL Server, PostgreSQL, SQL reporting logic, Excel, structured data analysis and data-flow investigation.
Other systems and reporting environments can be assessed during an initial discussion to determine whether SchemaHelm is the right fit.
Practical by design
SchemaHelm is built around practical investigation rather than guesswork.
The aim is to identify what is going wrong, clarify how the data and reporting processes actually work and help restore trust in the numbers.
Clients receive clear findings, prioritised actions and a practical route towards stronger reporting foundations.
Why it matters
When data is spread across systems, spreadsheets and reporting tools, small differences in definitions, filters, calculations and manual processes can create conflicting results.
Over time, businesses may become dependent on workarounds, undocumented knowledge and repeated manual reconciliation.
Clearer structure, logic and source-of-truth understanding can support:
more reliable reporting
faster and more confident decision-making
reduced dependence on manual fixes
clearer ownership of data and definitions
safer automation
more trustworthy analytics and AI initiatives
SchemaHelm helps businesses strengthen the foundations beneath their reporting so they are better prepared for what comes next.
Background
SchemaHelm was founded by Dr Ian Kirby, a reporting and data specialist with experience across financial services, education and research.
Ian’s background includes SQL, reporting logic, systems analysis, data validation, data-flow investigation and diagnosing why reports or systems produce unexpected results.
SchemaHelm grew from a simple observation: many businesses do not lack ambition, technology or ideas.
They lack a clear and trusted understanding of the data beneath their reporting.
When data is messy, systems are disconnected and logic is unclear, reporting becomes harder to trust, decision-making becomes riskier and future automation can amplify existing problems rather than solve them.
Principles
Clarity over confusion
SchemaHelm helps businesses understand how their data, reporting logic, systems and manual processes connect.
Practical over performative
The focus is on genuine reporting problems and usable findings, not vague transformation theatre.
Evidence before assumptions
SchemaHelm follows the reporting trail and examines the underlying data, definitions and logic before recommending what should happen next.
Trusted foundations first
Before reporting, automation or AI can be relied upon, the data underneath needs to be understood, controlled and sufficiently trustworthy.
Honest boundaries
Where specialist platform engineering, security or implementation expertise is required, SchemaHelm will identify that clearly and help define the appropriate next step.