Data visualization services that answer one question per chart Dashboards designed around the questions your managers ask every week
Data visualization consulting, from the question to the chart Dashboards people read in a minute and act on the same day
How our data visualization services work From the questions your managers ask to dashboards they open every week
- Week 1Gather requirementsWe list the questions each team asks, and the decision each answer serves.
- Week 2Agree the modelA project, a team, or ongoing reporting support, and the tool to build in.
- Weeks 3 to 6Design the analyticsSketches first, then dashboards built on real data with the people who'll use them.
- Before launchTest and QAEvery figure is checked against its source, and every page against its load time.
- LaunchOnboard and documentShort training for each team, and a definition for every number on the page.
When data visualization services are the right fit And when the data or the definitions need fixing first
A good fit when
- Your data is in good shape, but people can't find answers in the reports
- Teams rebuild the same report in Excel every Monday
- A dashboard has 40 charts and nobody knows which one matters
Look elsewhere when
- Two systems disagree on the number: start with data engineering
- Nobody agrees what the number means: start with data analytics
- You need a forecast, not a picture of the past: see AI and ML services
Our data visualization services in detail What each service covers, and what changes for the people who read the charts
Dashboard design and development
A good dashboard answers the few questions one team asks every week, at a glance. We start from those questions, choose the chart that answers each one fastest, and put the most important number where the eye lands first.
Bars for comparing, lines for trends, maps only when place matters, and tables when people need exact figures. Every chart has a title that says what it shows.
Automated reporting and analytics
Many teams spend Monday morning exporting data and rebuilding the same report. We automate it: the data refreshes overnight, the report updates itself, and it arrives in the right inbox or Teams channel before the meeting.
BI tools implementation
We build in the tool that fits where you run: Power BI for Microsoft companies, Tableau for teams that explore data visually, Looker on Google Cloud, or Qlik. If your managers already open a tool every day, we usually keep it.
Data visualization optimization
Dashboards slow down and fill up over time. We cut load times by fixing the model underneath, remove charts nobody reads, and check colors and labels so the dashboard works for people with color blindness and on a phone.
- Load times under a few seconds
- One definition behind every number
- Readable on a laptop and a phone
Data preparation, integration and visualization in the cloud
Charts need clean, joined data. We connect your sources, prepare the data in a model built for reporting, and host it in Azure, AWS or Google Cloud, so dashboards stay fast as the data grows.
Data visualization for your industry
The charts that matter differ by industry, so we start from the decisions each one makes.
- Transportation and logistics: on-time delivery by carrier and lane
- Retail: stock by store, and sales against forecast
- Healthcare: bed occupancy, wait times and claims denied
- Energy and utilities: outages, usage and asset health
- Manufacturing: yield, scrap and machine downtime
Questions about data visualization services What buyers ask us before they start
Why is data visualization important?
People see a pattern in a chart in seconds that they'd miss in a table of thousands of rows. Good visualization means decisions are made on facts, by more people, sooner.
Are information visualization and data visualization the same thing?
They overlap. Data visualization shows numbers as charts to reveal trends and patterns. Information visualization is broader, and includes non-numeric information such as processes and relationships, often as diagrams or infographics.
What's the difference between data mining and data visualization?
Data mining uses statistics and machine learning to find patterns in large data sets. Data visualization shows data, or those patterns, as charts people can read and act on.
What are the different types of data visualization?
Charts, graphs, tables, maps, infographics and dashboards. Each suits a different question: comparisons, trends over time, parts of a whole, places, or relationships between measures.
How do I choose a data visualization company?
Look for one that starts from your decisions rather than your data, works in the tools you already own, and checks every figure against its source. Ask to see a dashboard they retired as well as one they built.
Bring the dashboard nobody opens
We'll show you which questions it should answer, and redraw one page in a working session.