Services

SchemaHelm provides practical support for businesses dealing with unreliable reporting, unclear data flow, disconnected systems, spreadsheet workarounds and fragile reporting logic.

The focus is on understanding where reporting problems come from, why different outputs do not agree and what should be fixed first.

SchemaHelm works across databases, spreadsheets, structured data extracts and reporting processes, with current core expertise in SQL Server, PostgreSQL, SQL reporting logic, Excel and data-flow analysis.

How SchemaHelm approaches messy reporting problems

SchemaHelm does not begin by guessing or recommending a new platform.

The work starts by understanding where your data originates, how it moves, where it changes and why reports, dashboards or spreadsheets may be showing different answers.

The aim is to give your business:

  • a clearer view of the problem

  • an explanation of the underlying causes

  • a prioritised action plan

  • stronger foundations for trusted reporting

  • better preparation for future automation and AI

Messy Data Diagnostic

A focused investigation into where reporting confusion, inconsistency, duplication and risk are coming from.

This service helps with:

  • conflicting reports and inconsistent numbers

  • duplicate, missing or invalid records

  • inconsistent categories or business definitions

  • spreadsheet workarounds and manual fixes

  • weak validation and reporting controls

  • hidden reporting risks and weak processes

Why it matters:

When reporting problems are not clearly understood, businesses often spend time correcting individual outputs without addressing the underlying cause.

Outcome:

A clear summary of the main problem areas, likely causes, key risks and recommended priorities for further investigation or remediation.

Schema & Data Flow Mapping

A structured view of how data moves between source systems, databases, tables, files, spreadsheets, reports and manual processes.

This service can help with:

  • identifying source systems and reporting dependencies

  • understanding how data moves and changes

  • locating manual intervention and uncontrolled adjustments

  • exposing fragile handoffs between systems or teams

  • documenting important transformations

  • identifying potential sources of truth

Why it matters

When the reporting journey is unclear, business logic becomes harder to explain, maintain and trust.

Important knowledge may also become concentrated in one person or remain undocumented.

What you receive

Depending on the agreed scope, this may include:

  • a mapped reporting or data flow

  • key system and process dependencies

  • identified transformation points

  • areas of manual risk

  • source-of-truth recommendations

  • priorities for documentation or improvement

REPORTING RECONCILIATION AND LOGIC REVIEW

A detailed review of why reports, dashboards or spreadsheets do not match and where their underlying logic begins to diverge.

This service can help with:

  • mismatched metrics and conflicting outputs

  • different definitions of the same measure

  • unclear joins, filters or calculations

  • duplicated or excluded records

  • inconsistent date logic

  • manual spreadsheet adjustments

  • SQL and reporting logic that is difficult to explain or maintain

Why it matters

When key reports disagree, confidence drops and decision-making becomes slower, riskier and more dependent on manual checking.

What you receive

Depending on the agreed scope, this may include:

  • a reporting discrepancy register

  • an explanation of where figures diverge

  • identified differences in logic or definitions

  • recommended metric definitions

  • source-of-truth guidance

  • a prioritised remediation plan

AI DATA-READINESS ASSESSMENT

An assessment of whether the data and reporting foundations beneath a proposed AI or automation initiative are sufficiently clear, reliable and controlled.

This service can help with:

  • unclear or inconsistent business definitions

  • undocumented data sources

  • weak data quality controls

  • inaccessible or fragmented data

  • reporting logic that cannot be confidently explained

  • uncertainty about which data should be used

  • identifying risks before an AI project begins

Why it matters

AI tools cannot create trustworthy results from data that is poorly understood, inconsistently defined or unreliable.

Starting with the foundations can reduce risk, wasted investment and false confidence in automated outputs.

What you receive

A practical assessment of current readiness, key risks, information gaps and the work required before progressing with a proposed AI or automation use case.

This service focuses on assessment and roadmap development rather than advanced AI implementation.

WORKING ACROSS THE REPORTING CHAIN

SchemaHelm can investigate problems involving:

  • 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

Other systems and reporting environments can be assessed during an initial discussion to determine whether SchemaHelm is the right fit.

Where specialist platform engineering, security or implementation work is required, SchemaHelm will identify that clearly and help define the appropriate next step.

Not sure which service fits?

You do not need to diagnose the problem before getting in touch.

If you are dealing with conflicting reports, unclear data flow, disconnected systems, spreadsheet workarounds or reporting logic that is becoming harder to trust, briefly describe what is happening.

SchemaHelm can help determine the most appropriate starting point.