Tutorial — Using the Raw Data Explorer

What This Tool Is For

How to inspect the original data arriving from each connected source — the ground floor under every aggregated number.

Step-by-Step Walkthrough

Step 1 — Open the explorer and pick a source tab: each connected origin (cloud billing, payments, analytics, manual entries, and so on) has its own view of raw, untransformed records.

Step 2 — Use it for verification, not browsing: you come here when an aggregate looks odd and you want to see the underlying entries exactly as they arrived.

Step 3 — Check freshness: each source shows when it last delivered. A stale source explains a flat-looking metric faster than any theory.

Step 4 — Trace one number end-to-end occasionally as a habit: pick a figure on a dashboard, find its raw constituents here, and confirm they sum. Ten minutes a month of this builds justified trust in everything else.

Real-World Example

Scenario: June's cloud costs look implausibly low. In the explorer, the cloud tab shows its last delivery was June 19 — the feed went quiet for the final ten days. Nothing is wrong with the numbers that arrived; days are simply missing. The team notes the gap, the missing days arrive with the next delivery, and June's total settles correctly — diagnosed in five minutes from the raw view, instead of a day of doubting the entire pipeline.

Tips & Common Mistakes

• "Aggregate looks weird → check raw and freshness" should become a reflex; it resolves most mysteries in minutes.
• Manual entries live here too, with their author and attachment — the first place to look when a human-entered figure is questioned.
• Don't edit your way out of source anomalies; note them, fix the source, let corrected data flow.

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Everything described in this tutorial is a working feature of TupicFinance, the financial management platform of the Tupic ecosystem. The screens, workflows, and guardrails above behave exactly as written there — this guide doubles as the platform's user manual for this tool.