Services
Five ways SchemaHelm can help you understand, strengthen and maintain your data and reporting foundations.
Whether you are trying to understand why reports disagree, map how data moves through the business, prepare for a new system or AI initiative, or simply keep existing reporting healthy, the starting point depends on what you already know about the problem.
Not sure where to start? Describe what is happening and I will tell you which service is the best fit, or tell you honestly if SchemaHelm is not the right solution.
1. Messy Data Diagnostic
Start here if: something is clearly wrong with your reporting but you cannot yet say exactly what.
A focused investigation into where reporting confusion, inconsistency, duplication and risk are coming from.
What I look at
conflicting reports and inconsistent figures
duplicate, missing or invalid records
inconsistent categories or business definitions
spreadsheet workarounds and manual fixes
gaps in validation and reporting controls
processes that depend on undocumented knowledge
What you receive
A written summary of the main problem areas, the likely underlying causes, the key risks to your reporting and a ranked list of what should be addressed first.
Why it matters
Without a clear diagnosis, businesses can spend months correcting individual reports while the underlying cause continues producing new problems.
Scope and timescale agreed before work begins.
2 Schema & Data Flow Mapping
Start here if:you need to understand the wider reporting picture before committing to a system replacement, reporting project or transformation programme.
A structured map of how data moves between source systems, databases, tables, files, spreadsheets, reports and manual steps.
What I look at
source systems and reporting dependencies
how data moves and where it changes
points of manual intervention and uncontrolled adjustment
fragile handoffs between systems or teams
undocumented transformations
candidate sources of truth
What you receive
Depending on the agreed scope, this may include:
a mapped data flow
key system and process dependencies
key transformation points identified
areas where manual work creates risk
source-of-truth recommendations
priorities for documentation or improvement
Why it matters
When the reporting journey is undocumented, business logic can end up living in one or two people's heads. That is a continuity risk as well as a reporting risk.
Scope and timescale agreed before work begins.
3 REPORTING RECONCILIATION AND LOGIC REVIEW
Start here if:two reports, dashboards or spreadsheets disagree and you need to understand why.
A detailed review of where their underlying logic begins to diverge.
What I look at
mismatched metrics and conflicting outputs
competing definitions of the same measure
joins, filters and calculations
duplicated or excluded records
inconsistent date logic
manual spreadsheet adjustments
SQL or reporting logic that is difficult to explain, maintain or validate
What you receive
Depending on the agreed scope, this may include:
a reporting discrepancy register
a plain-English explanation of where and why figures diverge
differences in logic and definitions set out clearly
recommended metric definitions
source-of-truth guidance
a prioritised remediation plan
Why it matters
When key reports disagree, confidence drops quickly and decision-making becomes slower, riskier and more dependent on manual checking.
Scope and timescale agreed before work begins.
4 DATA READINESS FOR NEW SYSTEMS, AUTOMATION & AI
Start here if: you are preparing for a new system, system replacement, automation or AI initiative but are not confident that the existing data and reporting foundations are ready.
An assessment of whether the data, definitions, ownership, reporting logic and existing processes beneath the proposed initiative are sufficiently understood, reliable and controlled to build on.
What I look at
unclear or contested business definitions
undocumented or poorly understood data sources
duplicate, missing or inconsistent data
weak or absent data-quality controls
fragmented or inaccessible data
uncertainty about which data or source should be trusted
unclear data ownership and accountability
reporting logic that cannot be confidently explained
manual processes and spreadsheet workarounds
dependencies between existing data and proposed new systems
risks that could be carried into a system replacement, integration, automation or AI initiative
What you receive
A practical readiness assessment covering:
current readiness
key data and reporting risks
information and documentation gaps
important system and data dependencies
areas requiring remediation
source-of-truth considerations
recommendations for clearer data ownership and accountability
priorities for strengthening the data foundation
a practical roadmap for what should be addressed before the proposed initiative proceeds
Why it matters
New technology does not automatically fix existing data problems.
If a new system, integration, automation or AI initiative depends on data with conflicting definitions, unclear ownership, duplicated records or poorly understood reporting logic, those problems can be carried into the new environment.
Assessing the foundations first helps identify what can be trusted, where clearer ownership is needed and what should be addressed before further complexity is added. This can reduce migration problems, wasted investment, unreliable reporting and avoidable risk.
The aim is not to make every piece of existing data perfect. It is to understand what matters to the proposed initiative and establish a stronger foundation to build on.
This service covers assessment, recommendations and roadmap development. It does not include specialist system implementation or advanced AI implementation.
Scope and timescale agreed before work begins.
5 OPTIONAL REPORTING HEALTH CHECKS
After the initial work is complete, I can return on a six-monthly or annual basis to review whether reporting logic, definitions and data processes are still working as intended.
These reviews can help identify:
new spreadsheet workarounds
reporting logic that has drifted
undocumented changes
recurring data-quality issues
areas where previous controls are no longer working as expected
What you receive
A short independent health-check report with practical recommendations for anything that needs attention.
This keeps SchemaHelm involved without turning it into a permanent outsourced data team.
WHAT I WORK WITH
Systems and environments
I work with:
SQL Server and PostgreSQL
SQL reporting logic
Excel and manual reporting processes
structured data extracts and CSV files
database schemas and relationships
reporting definitions and calculations
data moving between business systems
data-quality and validation issues
If your environment is not listed, ask.
I will tell you during the initial discussion whether I am the right person for the work, and if I am not, I will say so.
Where specialist platform engineering, security or implementation expertise is required, I will identify that clearly and help define the appropriate next step.
NOT SURE WHICH ONE YOU NEED?
You do not need to diagnose the problem before getting in touch.
Describe what is happening in a few sentences and I will tell you where I would suggest starting.
If SchemaHelm is not the right fit, I will tell you that too.