← Portfolio

Yatify Data Reliability Monitor

The operational layer behind Yatify: source checks, release freshness, validation state, schema-change detection and a publish gate that protects dashboards from silent source failures.

LIVE SYSTEM
Decision
Know whether a dashboard is fresh and trustworthy before using its result.
Source
Yatify source-run logs + official source endpoints
Period
Continuous source checks
Created by
Nyashadzashe Munyati
CASE STUDY

The analytical result is shown before the technical method.

What I did in this project

01

Defined the question.

02

Prepared the data.

03

Built the analysis.

04

Validated and documented the result.

Know whether a dashboard is fresh and trustworthy before using its result.

A dashboard can look professional while being stale, incomplete or silently broken. The decision problem is whether today’s data products can be trusted.

02 · DATA

Source data

Yatify source-run logs + official source endpoints

03 · TRANSFORMATION

What I changed before calculating anything

04 · CALCULATION

Worked calculations — not black-box KPIs

05 · MORE ANALYSIS

What the drill-down adds

The headline chart gives the decision signal. These additional views show whether the same conclusion survives when the data is sliced another way.

Numerical visuals are added after the source data pass validation.

The question and method are documented, but unfinished results are not presented as completed analysis.

06 · INTERPRETATION

What I would say in the management meeting

07 · RECOMMENDATION

What I would do next

TRIGGER / EVIDENCEACTIONWHY
Analysis completeTreat data freshness and quality as first-class dashboard metrics, not hidden back-office work.Turn the finding into a decision.

Shared hosting cron setup is provider-specific and must be scheduled after upload. Stats SA source formats can change, so the source monitor detects new releases while parsing remains validation-gated.