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AI Solutions & Automation
AI assistants, document processing and RAG over your own data, built with clear guardrails and honest limits on what AI can do.
Dashboards built on clean, defined data
We agree what each metric means before building the dashboard, so the numbers your team sees are accurate and trusted.
Oneshot Digital Hub is a global technology services company that turns scattered spreadsheets and systems into dashboards in Looker Studio, Power BI or Metabase, built on data warehoused in PostgreSQL or BigQuery with clearly defined KPIs, for businesses in Nigeria, the UK, the US and Europe. You receive a working dashboard, documented data definitions and an honest view of data quality issues that need fixing.
- Deliverables
- Warehoused data, KPI definitions, dashboards and data dictionary
- Timeline
- 4–8 weeks
- Starting budget
- From $2,500
- Best for
- Teams needing one trusted view of their numbers
What does Data & BI include?
A dashboard is only as trustworthy as the data feeding it and the definitions behind each number. Many businesses have data scattered across spreadsheets, a CRM and an accounting tool, with no agreed definition of a basic term like active customer or monthly revenue, so two reports can show different totals for the same period. Fixing the definitions matters more than the chart type.
We warehouse your data in PostgreSQL or BigQuery, write the transformations that turn raw records into clean tables, and build dashboards in Looker Studio, Power BI or Metabase depending on what your team already uses. Every KPI is defined in writing before it appears on a dashboard, and we flag data quality problems rather than smoothing over them.
We start by agreeing a short list of KPIs that actually drive decisions, then trace each one back to its source data before building anything visual. Dashboards ship with a data dictionary explaining every metric, and we do not present forecasts or trends with more confidence than the underlying data supports.
KPI definition workshop
An agreed, written definition for every metric before it appears on a dashboard.
Data warehouse setup
Data consolidated into PostgreSQL or BigQuery from spreadsheets and existing systems.
Data transformation pipelines
Automated processes turning raw records into clean, consistent tables ready for reporting.
Dashboard build
Working dashboards in Looker Studio, Power BI or Metabase, matched to your existing tools.
Data quality report
A documented list of data quality issues found, with a plan for fixing each one.
Data dictionary
A written reference explaining exactly what each metric on the dashboard measures.
Access and permission setup
Dashboard access controlled so each team member sees only the data relevant to them.
Documentation and handover
A written guide covering the data pipeline, the dashboards and how to add a new metric.
Who is Data & BI for?
Sales dashboard for a Lagos distributor
A Lagos distributor wants stock, sales and reorder data in one dashboard instead of three spreadsheets.
Operational reporting for a UK firm
A UK firm wants weekly reporting on utilisation and revenue pulled automatically from its existing tools.
Executive dashboard for board reporting
Leadership needs a single accurate view of revenue, costs and pipeline for board meetings.
Data cleanup before a BI rollout
A business with years of inconsistent spreadsheets needs the data cleaned before any dashboard is built.
- One agreed number for each key metric
- Dashboards built on clean, warehoused data
- Data quality issues surfaced instead of hidden
- Reporting your leadership team can act on
How does the work run?
01
Discovery and alignment
We learn what you want to change, who it affects, and confirm the goal and scope in writing.
02
Strategy and architecture
We plan the solution, stack and security model, then send a proposal with fixed scope, timeline and price.
03
Design and prototyping
You review wireframes or a clickable prototype and approve the direction before production code is written.
04
Engineering and development
We build in short, reviewed increments and show you working software in a weekly demo.
05
Security, testing and launch
Every release passes a security review, automated tests and a launch checklist before it goes live.
06
Continuous optimisation
After launch we monitor, measure and improve the system against the goal agreed at the start.
What does it cost?
From $2,500. Typical timeline: 4–8 weeks.
Prices depend on scope; every engagement gets a written fixed-price proposal after a discovery call. Data and BI projects typically start from $2,500, and Nigerian clients can pay in naira by bank transfer.
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FAQ
Questions about Data & BI
How long does a data and BI project take?
Most dashboard and warehousing projects take 4–8 weeks, depending on how many data sources need connecting. Your written proposal states the exact range for your project.
What does a data analytics project cost?
Prices depend on scope; every engagement gets a written fixed-price proposal after a discovery call. Data and BI projects typically start from $2,500, and Nigerian clients can pay in naira by bank transfer.
Which dashboard tool do you use?
We build in Looker Studio, Power BI or Metabase, usually matching whatever your team already has licences for, rather than introducing a new tool without reason.
Can you fix messy or inconsistent data?
Yes; we assess your existing data first and flag quality problems in writing, then clean and warehouse it before building any dashboard on top of it.
Do you make revenue or growth forecasts?
We build forecasting models where the underlying data supports it, but we state the assumptions and confidence level clearly rather than presenting a forecast as certain.