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Business Dashboards

How to connect Xero, Stripe and your other business tools to a dashboard

The four ways to feed a business dashboard, what goes wrong when data comes from several systems, how to keep access safe and the questions to ask before you build.

By Logic NI5 min read

Most dashboard problems aren't about charts. They're about data: getting the right numbers out of your accounting software, payment provider, CRM, booking system and spreadsheets, and making them agree with each other. This guide explains the ways to connect them, what goes wrong and how to keep it safe. For the wider picture, read the complete guide to business dashboards.

Where the numbers usually live

A typical Northern Ireland small or medium business has its numbers in several places:

Area Typical source What you'd want from it
Money in and out Accounting software such as Xero, QuickBooks or Sage Invoices, payments, overdue amounts, cash position
Card and online payments A payment provider such as Stripe, or card terminals Takings, refunds, payouts
Customers and enquiries A CRM, your website forms or a shared inbox New enquiries, quotes sent, wins and losses
Bookings and jobs A booking system or job management software Bookings, capacity, jobs by status
Orders and stock A shop platform or stock system Orders, stock levels, returns
Website and marketing Analytics, ad platforms Visits, where enquiries come from
Everything else Spreadsheets Whatever never found a proper home

Many of these systems offer a way for other software to read their data, often through an API (a defined way for programs to talk to each other) or through exports. What each one offers varies, so check before you plan.

The four ways to feed a dashboard

Method How it works Reliability Effort Best for
Direct connection (API or native connector) The dashboard reads from the system automatically High, as long as the connection is maintained Medium to high to build Systems you rely on daily
Scheduled import An export is picked up and loaded on a timetable, such as nightly Medium to high Low to medium Systems with exports but no good API
Shared database Your systems write to one place the dashboard reads High Higher, usually part of a wider build A business building its own systems
Manual upload Someone uploads a file Low, depends on memory Low Last resort or one-off data

If a number matters, avoid manual upload. Anything that relies on someone remembering will eventually be out of date.

What goes wrong when data comes from several places

Problem Example What to do
Same thing, different names "J. Smith Ltd", "Smith J Limited" and "Smith, J" are one customer Decide a single identifier and match on it
Different definitions One system counts a sale on order, another on payment Agree the definition and apply it everywhere
Dates and time zones A late-evening order falls on different days in two systems Standardise on one date rule
VAT and currency One system shows figures including VAT, another excluding State clearly which the dashboard uses
Duplicates The same invoice imported twice Check for unique references on import
Gaps A day missing because a connection failed Alert when data hasn't refreshed
Changed fields A supplier changes how its data is shaped, and the dashboard breaks Have someone responsible for fixing it

Cleaning and joining the data is usually the largest part of a dashboard project. Treat it as real work, not an afterthought.

The spreadsheet in the middle

Many businesses have a spreadsheet behind the numbers, copied from one system and tweaked before anyone sees it. That is the weak link:

What was found Who found it Read it with care
Serious errors were found in 91% of 55 operational spreadsheets across five field audits (1995 to 2000), and about 83% of 163 spreadsheets across nine studies (1995 to 2008) Raymond Panko, summary of spreadsheet audits Counts errors "serious in the context of the spreadsheet's use". Thresholds varied between studies, and reviewers miss errors, so the true rate is probably higher. The audits are older, so treat this as a warning, not a current measurement

The practical advice is to feed the dashboard from the source systems, not from a copy someone maintains by hand.

Keeping access safe

A dashboard that connects to your accounts and customer records is a sensitive thing. Good practice:

  • Read-only access wherever possible. The dashboard should look, not change.
  • Least privilege. Connect only to the data the measures need.
  • Named, revocable access. Use credentials you can withdraw, and record who set them up.
  • Role-based views. The person booking jobs doesn't need payroll.
  • UK GDPR. Personal data on a dashboard is still personal data. Show names only where needed. See AI and UK GDPR for the data protection principles, which apply to dashboards too, and the ICO's guidance for organisations.
  • Offboarding. Remove access promptly when someone leaves or a supplier relationship ends.

Questions to ask before you build

  1. Which systems feed the dashboard, and does each one offer a reliable connection?
  2. Who sets up and holds the access, and is it read-only?
  3. How often does the data refresh, and what happens if it fails?
  4. How are customers and other records matched across systems?
  5. Who fixes it when a connected system changes?
  6. What data leaves your systems, and where is it stored?
  7. How will we check the dashboard against the source numbers? Reconcile at least the first few weeks against the original reports.

Check before you trust

When the dashboard first shows a number, compare it against the source system's own report for the same period. Differences are normal at first. They tell you where a definition or a join is wrong. Do this until the numbers match and you can explain any remaining gap.

Where Logic NI fits

Joining systems is a large part of what we do. We connect your real systems, agree the definitions, test the numbers against your own reports and run it as a managed service, so the dashboard stays accurate when a connected system changes. See the integrations service and the business dashboard service, or talk to us.

FAQs

Common questions

Can a dashboard pull data from Xero?

Usually, yes. Accounting software commonly offers a way for other software to read its data, or exports that can be imported on a schedule. A direct connection is the most reliable, and what's available depends on the system, so check before you plan.

Can a dashboard show Stripe or card payment data?

Typically yes, through the payment provider's own connection or export. You'll want to decide whether figures are before or after fees and refunds so they match your accounts.

Can I connect my spreadsheets?

Yes, but a hand-maintained spreadsheet is the weakest link. Where possible, feed the dashboard from the source systems and keep the spreadsheet for ad hoc analysis.

How often should dashboard data refresh?

Match it to the decision. A busy booking desk may need near-live data, while a weekly management view can refresh nightly. More frequent refreshing costs more to build and run.

Is it safe to connect my accounts to a dashboard?

It can be if access is read-only, limited to the data needed, recorded and revocable, and views are restricted by role. UK GDPR applies to personal data on a dashboard just as it does anywhere else.

What happens if a connected system changes?

The connection can break quietly. Someone, you or a supplier, needs to be responsible for noticing and fixing it. With a managed dashboard that should be part of the arrangement.

Sources

Every figure in this article comes from the sources below. Where a study measured something narrower than a headline suggests, the article says so.

  1. Department for Science, Innovation and Technology, Business data use and productivity study (wave 2): statistical report · Updated 28 January 2026. 3,796 UK businesses, fieldwork December 2024 to February 2025
  2. Raymond Panko, Audits of Operational Spreadsheets · Summary of field audits of working spreadsheets, 1995 to 2008
  3. Information Commissioner's Office, Guidance for organisations · UK GDPR and data protection guidance

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