QUA:1139: Update "Observability and Freshness" page as per your suggestions.

docs/checks/freshness-check.md

@@ -31,7 +31,56 @@ A **Freshness Check** monitors when a dataset (table, file, or view) was last up
    * **Pass** → Data is updated within the allowed time.
 
    * **Fail** → Data is older than the limit, triggering an **alert**.  
-
+
+## How Freshness is Measured Across Platforms
+
+Qualytics performs volumetric and freshness measurements differently depending on the data platform and container type (table, view, or computed).
+
+### Snowflake
+
+#### Tables
+
+Freshness and volumetrics are retrieved directly from the `INFORMATION_SCHEMA`. (System-level metadata is used — not the Incremental Field.)
+
+#### Views and Computed Objects
+
+- **Volumetrics:** `SELECT COUNT(*) FROM <object>`
+
+- **Freshness:** `SELECT MAX(<incremental_identifier>) FROM <object>` (Here, the Incremental Field defined in Table Settings determines freshness.)
+
+### Oracle
+
+#### Tables
+
+- **Volumetrics:** Retrieved from the `information_schema`
+
+- **Freshness:** Determined using `SELECT MAX(<incremental_identifier>)`
+
+#### Views and Computed Objects
+
+- **Volumetrics:** `SELECT COUNT(*) FROM <object>`
+
+- **Freshness:** `SELECT MAX(<incremental_identifier>) FROM <object>`
+
+### S3
+
+- **Freshness:** Based on the file modification time.
+
+- **Volumetrics:** Depends on file format.
+  - CSV, Excel → file load + row count.
+  - Delta or structured formats → row counts extracted from metadata.
+
+### BigQuery
+
+Same behavior as Snowflake:
+
+- **Tables:** Retrieved from `INFORMATION_SCHEMA`.
+- **Views/Computed:** `SELECT COUNT(*)` and `SELECT MAX(<incremental_identifier>)`.
+
+!!! note
+    - For regular tables, freshness is evaluated from `INFORMATION_SCHEMA` — the configured Incremental Field is not used.
+    - For views or computed tables, freshness is derived from the Incremental Field defined in Table Settings.
+
 ## Configuring Freshness Check
 
 **Step 1:** Log in into your Qualytics account and select the **datastore** from the left menu on which you want to add a volumetric check.

docs/observability/freshness.md

@@ -22,4 +22,7 @@ This measures the timeliness of data by monitoring when new data was last added
 |    14. |     **Maximum Age** | Displays the maximum recorded age of data in milliseconds. |
 |    15. |     **Last Asserted** | Shows the latest date when the data was validated or checked. |
 |     16. |     **Edit Maximum Age** | Edit **Maximum Age** lets users set custom limits for data freshness, allowing control over when alerts are triggered based on the age of the data. |
-|     17. |   **Graph Visualization** |  Graph illustrates consistent data patterns over time, with sudden anomalies marked by spikes in red. It reflects changes in data freshness and highlights when the data was last updated. |
+|     17. |   **Graph Visualization** |  Graph illustrates consistent data patterns over time, with sudden anomalies marked by spikes in red. It reflects changes in data freshness and highlights when the data was last updated. |
+
+!!! note
+    For more information please refer to the [**Freshness Check**](../checks/freshness-check.md) documentation..

mkdocs.yml

@@ -177,9 +177,9 @@ nav:
       - Overview: observability/observability.md
       - Observability Categories:
         - Measures: observability/measures.md
+        - Metric: observability/metric-check.md
         - Volumetric: observability/volumetric.md
-        - Freshness: observability/freshness.md
-        - Metric: observability/metric-check.md  
+        - Freshness: observability/freshness.md  
       - Manage Observability:
         - Overview: observability/manage-observability.md
         - Edit Check: observability/edit-check.md