Data analytics

Data analytics for companies means collecting data from operational systems, cleaning it and turning it into reports leadership can act on. Trust makes the difference: a dashboard whose figures do not match the ERP will not be used.

Problems it solves

  • The monthly report is built by hand and takes days.
  • Sales and finance report different numbers for the same month.
  • Data sits in five systems and nobody sees it together.
  • Nobody opens the dashboard you already have.

What the service includes

Data inventory

What data exists, where, who owns it and how accurate it is.

Data integration

Automated, scheduled and monitored pipelines from ERP, CRM, online store and other sources.

Data warehouse

A common data model with single definitions for every metric.

Operational dashboards

Few screens, built around the decisions their users make.

Data quality

Validation rules, anomaly alerts and named owners.

Metric definitions

A shared glossary: what "sale", "active customer" or "margin" mean in your company.

Example solutions

Monthly management report

Generated automatically, with the same figures for every department.

Sales and stock dashboard

By product, channel and region, refreshed daily.

Operations monitoring

Late orders, returns and exceptions, visible while they can still be fixed.

Technologies and standards

Tools follow data volume and who will use them. The principles stay the same:

  • Scheduled, monitored ELT/ETL pipelines
  • Dimensional model for reporting
  • Versioned metric definitions
  • Role-based access control

How we work

  1. First conversation

    We learn the problem, the systems you use and your time and budget constraints, and tell you honestly whether we are a fit.

  2. Analysis and proposal

    For larger work, a short discovery: scope, proposed architecture and a phased estimate with risks in plain view.

  3. Phased delivery

    We build incrementally with regular demos. Scope changes are discussed and estimated before they are made.

  4. Handover and support

    Documentation, training and full access to code and configuration. Then maintenance with clear terms, or in-house takeover.

We start with three to five business questions leadership wants answered, build the data and reports for those, then expand.

What you receive

  • Data inventory and assessment
  • Metric glossary
  • Automated data pipelines
  • Reporting data model
  • Dashboards and reports
  • User documentation

Business benefits

One version of the truth

Everyone reports from the same data and definitions.

Time back

The manual report becomes automatic.

Timely decisions

Deviations show while they can still be corrected.

Integration with existing systems

Analytics depends on good integrations. We start from existing flows and fill the gaps.

Security and maintenance

  • Report access follows company roles.
  • Personal data is pseudonymized where analysis does not need identity.

Frequently asked questions

Which BI tool do you use?

The one that fits your data volume and team. If you already license a tool, we start there.

Do we need a data warehouse?

Not always. For a few sources and small volumes a simpler model is enough. The inventory decides.

How often is data refreshed?

As often as decisions require: daily for most reports, more often for operations.

Useful guides

Related services

We start from the systems you already have

Tell us in a few lines what you want to solve. We reply with the right questions and a concrete next step.