Data & analytics
Data analytics & BI dashboards
Overview
Google Analytics setup, Power BI / Tableau dashboards, KPI tracking, and data visualization.
Delivery
Data analytics & BI dashboards Delivery Process
Discover
We map your business, your users, and what winning looks like before a single pixel.
Design
Direction, identity, and interfaces: shared early and reviewed with you at every step.
Build
Engineering in weekly slices you can see, click, and comment on as they land.
Launch
QA, performance, SEO, and deployment handled end to end. Nothing left to chance.
Grow
Support, iteration, and new capabilities as your business scales beyond launch day.
Details
Typical timeline
Per dashboard or monthly
Best for
Deliverables & Scope
- → Tracking implementation for GA4 or your warehouse, with events defined
- → Power BI, Looker Studio, or Tableau dashboard built on your data
- → Data model and metric definitions documented in plain language
- → Access set up for the people who need it, with row-level security where required
- → Training session on reading and filtering the dashboard
Post-Delivery
- → 30-Day Bug Warranty
- → Source Files & Ownership
- → Handover Training Session
Investment
Data analytics & BI dashboards Investment & Pricing
Indicative starting ranges - every project is quoted to its real scope.
FAQ
Data analytics & BI dashboards FAQs
How much does a BI dashboard cost?
US clients pay $800 to $4,000 and Australian clients pay A$1,200 to A$6,000 per dashboard. One dashboard on a single data source sits at the low end. A warehouse model feeding several role-based dashboards sits at the top.
How long does it take to build?
Two to five weeks. Getting reliable access to source systems takes the longest, followed by agreeing on definitions. The visual layer is usually the quickest part.
Who owns the dashboard and the data model?
You do. If we build it in your Power BI or Tableau account, it stays there. If we build a transformation layer, the code lives in your repository.
What happens after launch?
Dashboards drift as the business changes, so we recommend a review every quarter to add or retire metrics. Broken upstream data is the usual reason a dashboard goes stale, and that needs monitoring.
Why do our numbers disagree with what the CRM shows?
Because they are counting different things. Analytics tools attribute by session or last click, CRMs attribute by deal owner and close date, and timezone handling differs. We document which source is authoritative for each metric rather than trying to force them to match.
What is the difference between a dashboard and a report?
A dashboard is for monitoring: you glance at it weekly and spot what changed. A report is for a decision, with a narrative and a recommendation. A dashboard alone rarely changes behaviour, which is why we ask what decision each chart is meant to inform.
Do we need a data warehouse?
Not at first. Direct connections to your sources work fine for a handful of dashboards. A warehouse becomes worthwhile once you have several sources, slow queries, or a need for historical snapshots that the source systems do not keep.
Ready to start your project?
Start this project