---
title: "Data Hub: Data Onboarding"
url: "https://ensights.productfruits.help/en/article/data-hub-data-onboarding"
language: "en"
last_updated: "2026-08-25T13:21:36.802Z"
---

# Data Hub: Data Onboarding

A completeness score per system, so you can see which setup fields are missing before they distort a report.

## What this page is for

A connector brings in readings. Data Onboarding tells you whether the *context* around those readings has been filled in — capacity, location, expected production, financial terms, warranty dates.

That distinction is the whole point of the page. A site with readings but no expected production will show you kilowatt-hours, but the platform cannot tell you whether that figure is good or bad, cannot compute a performance ratio, and cannot raise a meaningful underperformance alert. The data is there; the judgement is not.

So this page is the honest answer to "why does this site have no performance figures?" It is almost always a missing field rather than a missing reading.

![The Data Onboarding page: total systems, average completeness, complete count and a distribution bar across the Critical to Complete bands, above a table of systems sorted least complete first.](https://cdn-assets.productfruits.com/27a44926-a7cb-41d6-ad2e-aa2cd0f60e7c)

## The summary row

| Figure | Meaning |
| --- | --- |
| Total Systems | How many systems exist in the account. |
| Avg. Completeness | The average score across them, with its band label — for example 20%, Critical. |
| Complete | How many systems are fully complete, out of the total. |
| Distribution | A stacked bar with counts in each band: Critical, Low, Fair, Good and Complete. |

A note under the heading says how many systems the figures are based on and how they are sorted — least complete first by default, which is the order you actually want to work in.

## The bands

Five bands, from **Critical** through **Low**, **Fair** and **Good** to **Complete**. The filter chips above the table carry a count each, so you can jump straight to a band — clicking *Critical* narrows the list to the systems most worth fixing.

## The table

| Column | Meaning |
| --- | --- |
| System Name | The system, shown with its vendor logo. |
| System ID | The internal identifier, truncated. |
| Capacity (kWp) | Installed capacity, or a dash where it has not been entered. A dash here is itself a completeness problem — capacity underpins most normalized metrics. |
| Completeness | A progress bar, the percentage, and the band label. |

Above the table: a search box and the system count. The preferences button at the right lets you toggle the System ID, Capacity and Completeness columns, with **Toggle All** and **Reset to defaults**.

![The Data Onboarding column preferences menu, with toggles for System ID, Capacity and Completeness plus Toggle All and Reset to defaults.](https://cdn-assets.productfruits.com/c3744f7e-edeb-4fd6-82b2-264e5741b459)

## The per-system view

Clicking a row opens that system's edit page with an **Onboarding completeness** banner at the top — for example "8 of 79 scorable fields complete" — and a percentage for each tab down the left: General, Advanced, Performance, Integrations, Financials, Alerts Management, Products & Warranties, Inventory, Obligations.

![A system opened from Data Onboarding: an Onboarding completeness banner reading 8 of 79 scorable fields complete, with per-tab percentages for General, Advanced, Performance, Integrations, Financials, Inventory and Obligations, and markers beside each scorable field.](https://cdn-assets.productfruits.com/03c872e4-0441-4f6d-a461-c29513e74708)

Inside a tab, each scorable field carries a small marker: filled where the field is complete, hollow where it is included in the score but still missing. Hovering tells you which. This is what turns a percentage into a to-do list — you can see exactly which fields are pulling the score down rather than guessing.

The tab percentages tell you where the effort is best spent. A system at 45% on General but 0% on Performance will never produce a performance ratio, however much else is filled in.

## How to improve a system’s score

1.  Go to **Data Hub → Data Onboarding**. The least complete systems are already at the top.
2.  Click the system with the lowest score, or the one you care about most.
3.  Look at the per-tab percentages and start with the tab that blocks what you need — **Performance** for expected production, **Financials** for revenue figures, **General** for capacity and location.
4.  Fill in the fields marked as missing.
5.  Press **Save**. The score recalculates.

## Which fields matter most

Not every field carries the same weight in practice, whatever it contributes to the percentage:

-   **Installed Capacity DC** — without it, nothing can be normalized. Almost every comparison across sites depends on it.
-   **Location and coordinates** — needed for weather data, and therefore for anything weather-adjusted.
-   **Expected Production and Expected Irradiance** (the Performance tab) — the twelve monthly pairs behind Expected Weather Adjusted Power. Without them there is no expectation to compare against.
-   **Timezone** — gets daily boundaries right. Wrong timezone quietly shifts every daily figure.
-   **Financial fields** — needed before revenue appears anywhere.

## Notes

-   Completeness is about configuration, not data quality. A system can score 100% and still have a broken sensor.
-   A low fleet average is normal on an account that has grown quickly. Work down the Critical band rather than trying to reach 100% everywhere.
-   Fix onboarding *before* investigating a performance anomaly on that site. Half of anomalies on incomplete systems are the missing field, not the asset.
-   The page is titled *Onboarding Completeness* in the browser tab, and appears as **Onboarding Completeness** in the tenant feature list.