Dashboard Refresh
The BI Pixie Dashboard is a Power BI template app built on a semantic model that holds your BI Pixie telemetry. Each time Power BI refreshes the semantic model, Power BI reads the event data in your storage container and imports the latest events, so the dashboard shows them.
This page explains how dashboard refresh works, what limits apply to each plan, and how to get the most out of your refresh budget.
How It Works
BI Pixie continuously collects telemetry from your tracked Power BI reports and stores it in your dedicated storage container. The dashboard is a separate Power BI app that you schedule to refresh on a regular cadence, just like any other Power BI semantic model.
Each refresh pulls event data from your storage container and loads it into the semantic model. The amount of data loaded depends on two factors:
- Data retention is how long BI Pixie keeps telemetry data in your storage container.
- Dashboard refresh window (Pro and Enterprise plans) is how many days of historical data each refresh imports into the semantic model.
For example, on the Pro plan with 365-day retention and a 90-day refresh window, BI Pixie keeps a full year of raw data in storage, and each dashboard refresh loads only the most recent 90 days into the semantic model.
Refresh Limits by Plan
| Free | Standard | Pro | Enterprise | |
|---|---|---|---|---|
| Refreshes per day | One a day for the first 30 days after you first install the dashboard, then one a week | 2 | 4 | 4 |
| Data retention (max) | 30 days | 30 days | 365 days | 1,095 days |
| Dashboard refresh window | All data | All data | 7 to 365 days | 7 to 365 days |
| Refresh strategy | Full scan | Full scan | Full scan | Full scan. Incremental refresh and Direct Lake over the full retention are available when you move the pipeline to the Workload or to Azure Databricks, as described below. |
The refresh window cannot exceed your current retention period. For example, if your retention is set to 30 days, the maximum refresh window is 30 days.
What Happens When You Reach the Limit
BI Pixie tracks how many times your dashboard semantic model is refreshed each day. When the semantic model reaches its daily refresh limit, BI Pixie pauses further refreshes until the limit resets, and Power BI shows a message saying that your daily data refresh limit has been reached.
No telemetry data is lost during this time. BI Pixie continues collecting events from your tracked reports as usual. Once the limit resets, Power BI imports all the data collected in the meantime on your next scheduled refresh.
Tip: If you schedule your dashboard to refresh in the Power BI service, the number of scheduled refreshes needs to stay within your daily limit. For example, on the Standard plan with 2 refreshes per day, you can schedule the semantic model to refresh twice, once in the morning and once in the evening.
Optimizing Your Refresh
Use the Dashboard Refresh Window
On the Pro and Enterprise plans, you can configure the dashboard refresh window in the Data Management page. The refresh window sets how many days of historical data the semantic model imports on each refresh. The window is applied when the dashboard is installed or reinstalled, so a change takes effect after the next reinstall of the dashboard.
A narrower refresh window means each refresh processes less data and completes faster. A narrow refresh window is especially useful if you have a long retention period but only need the dashboard to show recent activity.
For example, a customer on the Pro plan tracking 10 reports with 365-day retention might set the refresh window to 90 days. The full year of raw data remains available for searches in the Data Management page, while the dashboard stays focused on the most recent quarter.
Schedule Refreshes Thoughtfully
You do not need to use all your daily refreshes. If your organization reviews the dashboard once a day, a single morning refresh may be sufficient. You can keep the remaining refreshes for days when you need more current data, such as after a major report launch.
Plans with More Refreshes
The Pro and Enterprise plans include 4 refreshes a day and a configurable refresh window. See Plans and Billing for details.
Scaling beyond the import refresh
The import refresh suits most data volumes. If you retain years of telemetry or track a large number of reports, you can move the telemetry pipeline to a Spark ETL that reads directly from your storage. Each ETL run processes only the new events, and the dashboard reads the result through Direct Lake, so there is no import step and no refresh timeout, however much data you keep. Two options run this ETL:
- BI Pixie Workload for Microsoft Fabric. If you use Microsoft Fabric, the Workload deploys the ETL notebook and a Direct Lake dashboard into your own Fabric workspace automatically. The Workload is the recommended option when you have a Fabric capacity.
- Power BI over Azure Databricks (Enterprise plan). If you already run Azure Databricks and do not use Fabric, the same ETL runs on your Databricks workspace, and the dashboard reads its output as an Import, DirectQuery, or Direct Lake semantic model.
With either option, the processed tables sit in your own environment, where you control access and governance, and you can extend the pipeline with custom measures, reports, or AI agents. BI Pixie support can help you choose the right option for your setup.
Data Is Never Lost
Regardless of your plan or refresh configuration, BI Pixie never stops collecting telemetry from your tracked reports. Dashboard refresh limits only affect how often the Power BI semantic model is updated. Your raw telemetry data is always available in your storage container and can be searched from the Data Management page.