Backendz Signal
One definition of every number, and dashboards people use.
A dedicated data & analytics team for numbers you can trust
Data engineers and analysts who bring your systems together, define each metric once and put it where decisions are made. When two reports disagree, this team settles it.
- Vetted in four stages
- In place within days
- Your codebase, your tools, your standups
- Code and IP transferred to you
- One UK company accountable
Trace every number to its source
Switch a source off and see which metrics it feeds. Pick a metric to read its one definition.
Sources
One warehouse, one definition per metric
5 of 5 sources flowing · tested for freshness and volume
Fed by ERP
Revenue
Invoiced amount, net of credit notes, by invoice date. Not orders, not cash received.
sum(invoice.net) - sum(credit_note.net)
Written once, agreed with the people who use it, and the only place any report gets this number from.
All metrics fresh.
Build the squad
The core roles are switched on. Add the others the work needs; we will propose the people for each.
Your Data & analytics team
3 roles, one accountable lead
Data engineer, Analytics engineer, Data analyst. Full-time or part-time each, for a sprint or the long term, in your codebase and your standups.
Plan this team with usWhat the Data & analytics team delivers
- Analytics consultingKPIs defined with the people who use them, and a reporting plan that follows.See the service
- Pipelines and warehousingData from every system in one place, tested for freshness and volume.See the service
- DashboardsReporting in Power BI or similar, built for the decision rather than the data.
- ForecastingDemand and capacity forecasts once the history underneath is trustworthy.See the service
Tools the team works in
Skills on the Backendz team today. We work in the stack you have unless there is a strong reason to change it.
Pipelines
- Python
- SQL
- Data pipelines
- Change data capture
- Scheduling
Warehouse
- Warehousing
- Transformation layer
- Data quality tests
Reporting
- BI
- Power BI
- Self-serve dashboards
Analysis
- Forecasting
- Statistics
- Experiment analysis
From first call to first sprint
Your team in place within days. Working software at the end of the first sprint.
- Scope callThirty minutes on what you are building, what is in place and what the team needs to own.
- Line-upWe propose the roles and the people, with their experience, and you meet them before anything is signed.
- OnboardingAccess, environments and the first tickets agreed. The team joins your tools and your standups within days.
- First sprintWorking software at the end of it, reviewed with you. The team grows or shrinks with the work from there.
How we vet engineers
Four stages, before anyone joins your work. You meet the people we propose before anything is signed.
- Portfolio & experience reviewRelevant projects, technical depth and hands-on experience are reviewed first.
- Technical assessmentA practical task tests code quality, problem-solving and the stack the project uses.
- Quality & team reviewSenior engineers review the work for implementation quality, communication and collaboration.
- Final approvalConfirmed against the project's requirements and Backendz's quality standards before joining a team.
Engage the way the work needs
- Dedicated teamA full squad owns an outcome: a product, a platform or a programme of work, with a lead who answers for delivery.
- Team extensionEngineers join the team you already have, in your codebase, your tools and your standups.
- Full-time or part-timeEach person is assigned for the hours the work needs, not a fixed block.
- A sprint or the long termStart with one sprint to prove the fit, then keep the team for as long as the roadmap runs.
Questions we are asked
What does a dedicated data & analytics team do?
It brings data from your systems into one warehouse, defines every metric once with the people who use it, and delivers the dashboards and forecasts built on top.
Why do our reports disagree, and can the team fix it?
Usually because two systems define the same word differently. The team agrees each definition in writing, implements it once in the transformation layer and points every report at it.
Which BI tools do you work with?
Power BI and similar tools. We use what your people already open each morning rather than adding another login.
How do we know the data is right?
Pipelines carry tests for freshness, volume and consistency, with alerts that reach a person when one fails.
Can the team build forecasts as well?
Yes, once the history is reliable. A data scientist joins the team to build demand or capacity forecasts on the same warehouse.
Services this team delivers
Hire individual developers
Still running on workarounds?
Book a 30-minute call with an engineer. Tell us what's breaking and we'll tell you what we would build, how long it would take and what it would cost, before you commit to anything.
