Turn business knowledge into an AI-ready data plan
ReadyMyData guides you through the questions, metrics, data sources, definitions and rules your data needs — so it can be used properly with dashboards, reports, AI tools, chatbots, copilots and whatever comes next.
The problem
Your data is the asset. Tools are just the interface.
Most businesses know what they want to understand — but they struggle to brief it clearly enough for anyone to build it. Important knowledge lives in people's heads, spreadsheets, old reports and scattered systems. When that knowledge is not written down, dashboards and AI tools can give confusing or wrong answers.
Business knowledge is scattered
Data definitions, business rules and reporting requirements live in people's heads, emails and spreadsheets — not in a single place the data team can read.
Tools cannot guess your meaning
Dashboards, AI assistants and chatbots will try to interpret your data — but if the definitions are missing or unclear, they will guess. And guesses can be wrong.
Prepare once. Use it anywhere.
When the business meaning is clearly written down, the same definitions and context can support dashboards, reports, AI tools and future systems — without starting from scratch each time.
What gets captured
Ten things the guide helps you define
Each step is written in plain English — no data engineering knowledge required.
What the business wants to understand
What decisions does this data need to support? What would success look like? Starting with the business goal, not the technical solution.
The questions people want to ask
What do people actually want to know? Capturing real questions in plain English — the kind someone would type into a chatbot or ask a colleague.
Key metrics and what they mean
What does "Revenue" mean in your business? What counts as an "Active Customer"? Agreeing definitions before anything is built prevents rework later.
Where the data comes from
Which systems hold the data? Is it in a spreadsheet, an accounting system, a CRM or a data warehouse? Knowing the source is essential before building anything.
Who owns the definitions
Who in the business is responsible for each metric or data area? Ownership prevents conflicting definitions appearing across different reports.
Business rules and exceptions
Are there edge cases, exceptions or special calculation rules the data team needs to know? These are the things that live in people's heads and break reports when missed.
Access and security considerations
Who should be able to see which data? Any sensitivity, compliance requirements or access restrictions that affect how the data can be used.
Dashboard and report needs
What does the output need to look like? How often should it update? Who will use it and on what device?
Conversational AI questions
If someone were to ask an AI assistant questions about this data, what would they ask? These examples help prepare the data for AI-assisted querying.
UAT and sign-off criteria
How will the business know the data and reports are correct? What needs to be tested, and who needs to approve the output before it goes live?
The bridge
From business need to technical brief
Business users should not need to know how to design a data model. But data teams, developers and consultants still need clear instructions. ReadyMyData helps translate business knowledge into a brief that anyone can build from.
Business goal
What does the business want to understand or decide?
Questions
What questions should the data be able to answer?
Metrics
What are the key measures and what do they mean?
Data sources
Where does the data live and who owns it?
Rules and ownership
What business rules and exceptions apply?
AI-ready guidance
Definitions, synonyms and context for AI querying.
Delivery pack
A complete brief your team or consultant can build from.
Planned output
The AI-Ready Data Delivery Pack
The guide is designed to produce a complete, practical pack that explains what the business needs, what questions the data should answer, what the key metrics mean, where the data comes from, what needs to be built, how it should be tested and how to make it ready for AI.
Prepare it once. Use the same definitions and context across dashboards, reports, AI tools, consultants and future systems.
Who it's for
For everyone who needs their data to work properly
Business owners
Get your data project started properly without needing to understand the technical side. Tell us what you want to know — we help you say it clearly.
Finance managers
Define what your revenue, cost and profitability metrics actually mean — so reports and AI tools calculate them the same way every time.
Operations managers
Capture the rules, exceptions and definitions that only exist in your head — before handing a brief to a developer or consultant.
Business users
Stop waiting for a developer to translate your question into a report. Start by writing down what you actually want to understand.
BI and data teams
Receive clearer briefs, stop rebuilding requirements from scratch, and spend less time asking stakeholders what they actually meant.
Consultants and freelancers
Run a structured scoping process with every client. Deliver a professional brief your team can build from and a client can sign off.
Project managers
Define scope, agree outputs and set sign-off criteria before a single line of code is written. Reduce rework and missed expectations.
When to use it
Common situations where this helps
"I need better reporting but don't know where to start"
The guide asks the right questions so you do not need to know the answers upfront. Just describe what you want to understand.
"I want to use AI to query my data"
Before your data can answer AI questions reliably, it needs clear definitions and context. The guide helps you capture those.
"I need a dashboard brief for a developer or consultant"
Walk through the guide and get a structured brief you can hand straight to whoever is building your reports.
"Our KPIs mean different things to different people"
The guide surfaces those differences before development starts — and helps you agree a single definition everyone will use.
"We are moving reports to a new tool"
Document what you have, what it means and how it should work — so the move does not mean starting from scratch.
"We want to avoid being locked into one vendor"
When your data definitions are written down and owned by your business, you can switch tools without losing the knowledge.
"We want to prepare our data before investing in AI"
AI is only useful if it understands your data. The guide helps you prepare the definitions and context AI tools need to give reliable answers.
Part of a wider toolkit
How the guide fits into ReadyMyData
ReadyMyData is building a complete toolkit for preparing data properly. The requirements guide is one part of that journey.
Define with the guide
Use this guide to capture business questions, metrics, data sources and rules before anything is built.
Start the guide →Assess with the scanner
Check whether existing data asset names, descriptions and structure are clear enough for people and AI to understand.
View the scanner →Get a delivery pack
The full AI-Ready Data Delivery Pack will be generated from your guide — a complete brief for developers, consultants or data teams.
View pricing →Get expert help
Need hands-on support? A manual review or requirements workshop can help prepare your data faster.
View services →The full guided workflow is being built
This page shows the direction, workflow and planned outputs for the AI-Ready Data Requirements Guide. The interactive step-by-step tool is being developed as the next major ReadyMyData feature.
In the meantime, you can use the current placeholder at /requirements or request help directly through Services — where a manual requirements workshop or data project review is available now.
The AI Readiness Scanner is available now and free to use — it checks whether your existing data asset names and structure are clear enough for AI tools and business users.
Ready to prepare your data properly?
Start the guide to begin capturing business knowledge, or get hands-on expert help preparing your data for AI tools, dashboards and future systems.