1. accoPLANNING shows exactly what Power BI sends
Explanation:
The accoPLANNING visual does not transform or modify the data it receives. It simply displays the values delivered through the Power BI custom visual API.
If you switch between the native Matrix and the accoTOOL visual, the results should generally match.
2. Native visuals and custom visuals use different APIs
Explanation:
Power BI’s native visuals operate using a different internal API than custom visuals.
Because of this, the two types of visuals may have different limitations, especially regarding row/column limits, data modeling, and performance.
3. Use “Show as table” to see the raw data returned to the visual
Explanation:
By selecting Show as table, you can view exactly the dataset Power BI provides to the custom visual — including hidden fields such as transaction keys.
This helps identify whether missing or unexpected values originate from Power BI’s data extraction process.
4. Row and column limits in custom visuals
Explanation:
The Power BI custom visual API currently enforces these limits:
Maximum 30,000 rows per visual
Maximum 100 columns in total
These limits do not apply to the underlying dataset — only to what Power BI actually sends to the custom visual after aggregations and filtering.
5. Large matrices give a poor user experience
Explanation:
Even if Power BI could technically send more data, matrices with thousands of rows (e.g., 1,000–35,000 rows) create usability problems in writeback scenarios:
Excessive scrolling
Poor performance
Difficult navigation
6. DirectQuery has a 1,000,000-row retrieval limit
Explanation:
When using DirectQuery, Power BI adds a TOP 1,000,000 limit to the SQL queries it generates.
This means:
Your table may contain many millions of rows
But Power BI will never load more than 1,000,000 rows per query
If the filtered subset exceeds this amount, data will be truncated