BI tools require IT, pipelines,
and technical setup.
ADAT requires an upload.
Tableau, Power BI, Looker, and Qlik are powerful visualisation platforms — for teams with data engineers, IT departments, and months to implement. ADAT visualises directly from any uploaded file. No clean data required. No IT request. No waiting.
Getting a chart should not
require a project plan.
Traditional BI tools were built for organisations with dedicated data teams. Before an executive sees a single chart, someone must connect data sources, build a pipeline, clean the data, model it, and publish a dashboard. That process takes days. Sometimes weeks. By then, the decision has often already been made.
The pipeline dependency
Tableau and Power BI connect to clean, structured data sources. They do not accept raw uploads and analyse them instantly. A data pipeline must exist before the visualisation can begin.
The IT dependency
Most BI deployments require IT involvement for data connections, user permissions, and server configuration. An executive who wants a chart must raise a request and wait in a queue.
The cost problem
Tableau costs $840–$3,000 per user per year — for visualisation alone. Power BI Premium reaches tens of thousands per month. And neither tool prepares your data or answers questions in plain English.
What each tool does —
and where the gap is.
Tableau
Industry-leading data visualisation. Powerful dashboards, deep chart customisation, broad data connectivity.
Gap: $840–$3,000/user/yr. Requires clean data sources. IT setup required. No plain English questions.
Microsoft Power BI
Business intelligence platform tightly integrated with Microsoft 365. Widely deployed in enterprise environments.
Gap: Requires Power Query knowledge. Data modelling required. Premium features cost significantly more.
Looker (Google)
Enterprise BI with a semantic layer (LookML). Governs metric definitions across the organisation.
Gap: Requires engineers to define LookML. Not accessible to non-technical users without significant setup.
Qlik Sense
Associative analytics engine. Explores relationships across data sets with AI-assisted discovery.
Gap: Complex data modelling required. Enterprise pricing. Steep learning curve for non-technical users.
Domo
Cloud BI platform with connectors, dashboards, and embedded analytics for business teams.
Gap: Connector setup required. No plain English query layer. Data must be pre-structured.
Metabase
Open-source BI tool. Self-hosted dashboards and simple SQL-based queries for smaller teams.
Gap: Requires database connection and SQL knowledge. No automated data preparation.
BI and visualisation tools vs
ADAT integrated visualisation.
| Capability | BI and visualisation tools | ADAT |
|---|---|---|
| Data preparation required | Yes — clean data pipeline must exist first | No — automatic from any upload |
| IT involvement needed | Yes — connections, permissions, setup | No — upload and visualise immediately |
| Plain English questions | Limited or none | Full natural language query layer |
| Time to first chart | Days to weeks | Minutes from upload |
| Cost | $840–$3,000+/user/yr visualisation only | From $40/mo — prep, visualise, ask included |
| Non-technical users | Requires training and technical support | Designed exclusively for non-technical users |
| Certified answers | Charts reflect data — no answer certification | Every result certified and auditable |
| On-premises option | Some — with significant IT overhead | Yes — cloud, on-prem, or desktop |
Your first chart is
minutes away.
Upload any file. ADAT reads the structure, prepares the data, and visualises it immediately. No IT request. No pipeline. No waiting.