ANALYTICS & REPORTING · SC-15
Tableau Commercial Analytics & Drill-Down
A Tableau-oriented commercial analytics system focused on interactive exploration, cohorts and drill-down behaviour.
Starting point
Reporting becomes noise when definitions differ, drill-down stops too early or nobody knows what decision follows the metric.
01 · BUSINESS PROBLEM
A dashboard is useful only when the KPI structure leads to an action.
Reporting becomes noise when definitions differ, drill-down stops too early or nobody knows what decision follows the metric.
Conflicting KPIs
Teams read different definitions for the same business question.
Static reporting
A top-line number does not reveal the driver underneath.
No next action
The report explains what happened but not where to investigate.
02 · DECISION LOGIC
From KPI to driver to action.
The information architecture follows the questions a manager actually asks.
Decision sequence
Each stage answers a different operating question
Read the state of the business.
Contrast plan, period or segment.
Locate the driver behind the variance.
Move from metric to management action.
Decision rule — The interface should shorten the path from question to decision.
03 · WHAT CHANGED
One semantic layer, multiple management questions.
Definitions live in the model; visuals expose them through a repeatable drill-down path.
Define KPIs once in the semantic layer.
Design filters around management questions.
Connect summary views to operational detail.
Keep refresh and data quality visible.
04 · ARCHITECTURE
A modular path from input to decision.
Inputs → preparation → core logic → validation → decision output
SC-15 · SYSTEM ARCHITECTURE
Inputs → preparation → core logic → validation → decision output
Public portfolio implementation
Inputs
Source signals
Capture the operating inputs required by the system. [Tableau]
Preparation layer
Normalize context and create a stable analytical contract. [LOD Expressions]
Core system
Core engine
Run the main analytical or automation logic. [SQL]
Decision logic
Apply the rule, model or orchestration logic that changes the decision. [PostgreSQL]
Validation
Validation
Test outputs against explicit quality criteria. [CSV]
Controls
Keep approvals, thresholds or constraints visible. [Calculated Fields]
Decision output
Decision output
Expose the result in a form the user can act on.
Monitoring
Record outcomes, exceptions and evidence for iteration.
Integration boundaries
Tableau
Defined responsibility inside the system; replaceable if another tool fits the requirement better.
LOD Expressions
Defined responsibility inside the system; replaceable if another tool fits the requirement better.
SQL
Defined responsibility inside the system; replaceable if another tool fits the requirement better.
05 · EVIDENCE & ECONOMICS
Measure what changes the decision.
Public implementation, inspectable technical proof and decision-focused validation.
Decision interface
KPIs
10
Representative public example.
Drill-downs
4
Representative public example.
Sources
6
Representative public example.
Information coverage
Decision views
3
Representative public example.
Target refresh
15m
Representative public example.
Reference economics
50 h
Reference scenario
40%
Illustrative improvement
20 h
Decision value
06 · TECHNICAL PROOF
Review the code behind the project.
Tools used
BUSINESS CONCLUSION
Good BI reduces the distance between a signal and a management action.
The value is not a prettier dashboard; it is a common definition layer and a faster path to the underlying driver.