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Fortlyn Technologies

Use case

Data & Analytics

Data platforms, governance and analytics that produce numbers the executive team is willing to act on.

Fewer dashboards, more decisions

The problem

What we hear consistently

  • Three systems, three answers, no agreed source of truth
  • Dashboards nobody opens because nobody trusts them
  • Data engineering effort consumed entirely by pipeline firefighting
  • Governance treated as a document rather than an enforced control

Typical outcomes

agreed definition per business metric
1agreed definition per business metric
of pipelines covered by quality contracts
92%of pipelines covered by quality contracts
more decisions traced to platform data
5xmore decisions traced to platform data

Figures are drawn from delivered engagements. Yours will differ — we will tell you what is realistic before you commit.

Our approach

How we actually go about it

  1. Define the metric before building the pipeline

    A semantic layer holds the agreed definition of every business metric. Reports read from it, so "revenue" means the same thing in the board pack and the operations dashboard.

  2. Contracts at the boundary

    Source systems publish against data contracts with schema and quality expectations enforced in CI, so breakages surface at the producer rather than in a report at month-end.

  3. Analytics where the work happens

    The numbers land in the tools people already use — the ERP screen, the command center, the daily operations review — not in a portal that requires a separate login and a reason to visit.

Evidence

Related customer stories

Talk to someone who has done this before

You will speak to a practitioner, not an account manager reading from a solution brief.