Analytics and visualization

Dashboards people actually open, and models that anticipate


A dashboard nobody opens is a cost, not an asset. We design for the decision first and the chart second — and where it pays off, we move from describing the past to predicting what comes next.

When this family makes sense


The services
01

Corporate dashboards

Designed around the decision

We start from the question the business needs answered, not from whatever data happens to be available. Then come the semantic model, the metrics and the visual layer.

What it covers

  • Workshops with the areas that will use it
  • Semantic model with certified metrics
  • Dashboard design and build
  • Row-level security by role and region
  • Adoption training

Deliverables

  • Dashboards in production
  • Documented metric definitions
  • Trained users

Tools and roles

Power BIQlikTableauSAP Analytics CloudAmazon QuickSightBI consultant

The payoff

The meeting starts from the numbers instead of arguing about them.

02

Predictive models

From what happened to what will happen

Demand forecasting, churn, predictive maintenance, credit and collections risk. Models built on governed data, with accuracy measured honestly against a real baseline and re-measured over time.

What it covers

  • Use-case definition with a business owner
  • Feature engineering and model training
  • Validation against a real baseline
  • Deployment and monitoring for drift

Deliverables

  • Model in production
  • Accuracy report against baseline
  • Retraining plan

Tools and roles

PythonDatabricksVertex AIAzure MLAmazon SageMakerData scientist

The payoff

You act before the problem arrives, not after the report shows it.

Scitis

Let's start by understanding what you need

The discovery call is free and ends with a recommendation of where to begin.

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