Data visualization and reporting
A dashboard nobody opens is a cost, not an asset. We build reports around the decisions people make each week, keep them fast, and make sure the same number means the same thing on every page.
Signs you could use this
- You have plenty of reports and people still export to Excel.
- Dashboards take a minute to load, or the numbers are a day late.
- Two reports show different totals for the same thing.
- Nobody can say who looks at a given dashboard, or whether anyone does.
What we do
- Find out what people use
- We talk to the people who read the reports and check the usage logs. Retiring unused reports is part of the job.
- Design with restraint
- A few well-chosen metrics, sensible comparisons, and drill-down for the people who want it. We avoid decoration that makes a chart harder to read.
- Build on a solid model
- Dashboards are only as consistent as the data model beneath them. We fix the model first so the numbers agree everywhere.
- Hand it over properly
- Documentation, a short training session and a support window, so the dashboards keep working after we leave.
What you receive
A first set of dashboards typically takes three to six weeks, depending on how clean the underlying data is.
- Dashboards built in your BI tool
- Metric definitions placed where users can see them
- A refresh schedule and basic monitoring
- A user guide and a training session
- Thirty days of support after launch
Tools we use: Power BI, Tableau, Looker, AWS QuickSight, Excel, BigQuery, AWS Redshift.
Common questions
Which BI tool should we use?
The one your team will actually maintain, and that fits your existing stack and budget. We have written a short guide to choosing between Power BI, Tableau and Looker in our Insights section.
Can you fix the dashboards we already have?
Yes. Often the quickest win is cleaning up an existing report: fixing the logic, speeding it up and removing what nobody reads.
Will our team be able to edit the dashboards?
That is the aim. We build in a way your team can follow, and we train them before we step back.