Before
Messy Input
CountryMetricValueOwnerKERevenue98%FinanceUGRev.0.98TZbudget ach.98 percentOps
Metric names, formats and owners differ by country, making regional comparison slow and easy to dispute.
Before / After Evidence Gallery
From messy operations to board-ready decisions.
This gallery shows the actual analyst craft behind the output: raw operational noise, the cleaned model, the dashboard layer and the final decision a leader can act on.
Gallery Flow
Each proof room follows the same four-step transformation.
Model
Cleaned Data Model
Dim CountryFact PerformanceMetric DictionaryRefresh Log
Definitions are standardised into country, time, metric and ownership layers with refresh status visible.
Dashboard
Performance View
Leaders can compare budget achievement, forecast risk and country-level performance without manual packs.
After
Decision Output
Decision:Prioritise two countries for variance review and standardise monthly metric sign-off.
The output becomes a management action, not only a visual report.
Before
Messy Input
CaseStageDateOfficer781review3/4/25A781Review04-MarA812pendingUnassigned
Duplicate case rows, blank dates and inconsistent stage labels hide the actual bottleneck.
Model
Cleaned Workflow Model
Case EventsStage OrderOfficer QueueSLA Calendar
Each case becomes a timeline with ordered stages, queue aging and owner accountability.
Dashboard
Bottleneck View
The dashboard surfaces where processing time accumulates and which queues need intervention.
After
Decision Output
Decision:Escalate cases aging beyond SLA and rebalance officer queues twice per week.
The evidence points to a clear operational rhythm, not a vague performance complaint.
Before
Messy Input
PDF
Clause 4.2... annex reference missing... donor rule repeated in appendix... budget note conflicts with paragraph seven...
Important obligations sit across long documents, annexes and repeated clauses, creating review fatigue.
Model
Grounded Review Index
ChunkSourceObligationRisk Tag
Documents are split into cited sections so generated answers stay connected to source material.
Dashboard
Risk Review View
HighMediumLow3714
Reviewers see obligation counts, unresolved clauses and where human approval is required.
After
Decision Output
Decision:Approve with three clarifications and attach cited risk notes before external submission.
The AI-assisted layer becomes a controlled review process with sources and sign-off.
Senior Analyst Signal
This is the part GitHub rarely proves.
The strongest analytics work happens between the raw file and the final chart: questioning definitions, cleaning edge cases, creating a model people trust, then turning the result into a decision cadence.
Raw inputAmbiguous, duplicated, incomplete
Model layerDefined, governed, explainable
Decision layerOwner, action, follow-up rhythm