RedSage Labs
RedSage Labs
Data Intelligence

Business Intelligence

Most companies do not lack data. They lack agreement on what the data says. We build the layer that ends the argument.

Business Intelligence is the discipline of turning operational data into answers people trust. We design the metric layer, the semantic models, and the reporting surface so that revenue, churn, and margin mean the same thing in every room - computed once, governed centrally, and served fast.

This is not a dashboard project. It is the rebuild of how your company agrees on numbers: definitions documented, lineage traceable, access controlled. When the foundation is right, every report downstream stops being a debate and starts being a decision.

The Challenge

The symptoms are familiar: three departments report three different revenue figures, analysts spend their week exporting and reconciling instead of analyzing, and every leadership meeting opens with an argument about whose number is right.

The cause is structural. Metrics live inside tools and spreadsheets instead of a governed layer, so every team computes its own truth - and no amount of new dashboard software fixes that.

Our Approach

We start with definitions, not tools: the twenty questions the business actually asks, the exact formula behind each answer, and the source of record for every input. That metric layer becomes the contract every report and dashboard builds on.

Then we engineer the pipeline and the semantic model around it - tested, versioned, documented. Adoption is part of the work: we sit with the teams who use the numbers until the new layer is where questions go to get answered.

Capabilities

Metric layer design: governed definitions for every number the business runs on.

Semantic modeling: one computation of each metric, served to every tool.

Executive and operational reporting built on the governed layer.

Self-serve analytics: teams answer their own questions without breaking the numbers.

Data quality monitoring: the layer flags bad inputs before they reach a decision.

Execution Process

01 //

Define

The questions, the formulas, and the source of record for every metric.

02 //

Model

The semantic layer engineered - tested, versioned, documented.

03 //

Build

Reports and dashboards rebuilt on the governed definitions.

04 //

Adopt

Teams migrated question by question until the old spreadsheets die naturally.

Business Outcomes

One version of every number, agreed before it is reported

Analyst time spent on analysis, not reconciliation

Meetings that start from the data instead of arguing about it

New reports in hours, because the hard part is already governed

Lineage you can show an auditor, an investor, or yourself

Deliverables

Governed metric layer with documented definitions
Semantic models covering core business domains
Executive and operational reporting suite
Self-serve analytics environment with guardrails
Data quality monitoring and alerting
Adoption plan, training, and documentation

Technologies

Semantic and metrics layers
SQL transformation pipelines
Warehouse-native modeling
BI and visualization platforms
Data quality testing frameworks
Version-controlled analytics code
Access control and row-level security

Frequently Asked Questions

Dashboards display numbers; they do not govern them. If each dashboard computes its own version of the metric, more dashboards means more disagreement. We fix the layer underneath - then the dashboards finally agree.

A governed metric layer for one core domain - typically revenue - takes weeks, not quarters. We expand domain by domain, each one immediately useful.

Usually not. Most tools work fine once the numbers underneath are governed. We recommend changes only when the tool itself is the bottleneck.

Business Intelligence

Reporting rebuilt as a decision system - one trusted set of numbers, answered questions, and no more spreadsheet archaeology.

Fix your reporting