BI Radar: Business intelligence updates for analysts
BI Radar tracks verified Power BI, Fabric, Snowflake, and Databricks business intelligence updates with practical guidance for analysts.
BI Radar
Learn about business intelligence. BI Radar tracks supported platform updates with monthly source-backed guidance to keep BI skills current after training.
Canonical vendor sources
BI Radar follows significant changes in supported tools such as Power BI, Microsoft Fabric, Snowflake, and Databricks. It reviews vendor documentation and official release notes, then publishes monthly summaries of verified changes that matter to BI workflows. Vendor schedules differ, so not every platform has a monthly release.
Methodology and editorial checks
Start with the official facts and source links. Distinguish generally available features from previews, announcements, and gradual rollouts; a feature mentioned by a vendor may not yet be enabled for every tenant or user.
Then consider the workflow implications: who would benefit, what needs to change, and what should be tested before adoption. Recommendations are context, not a substitute for validating behavior in your own environment.
Before and after: define a discount rule once, reuse it in two measures
A DAX user-defined function (UDF) is saved once as a model function and called by name from measures. This example reduces repeated discount logic; it demonstrates code reuse, not guaranteed faster query execution.
Before: each measure repeats the guarded discount calculation
[Net Sales] =
[Gross Sales]
* ( 1 - MIN ( 1, MAX ( 0, [Discount Rate] ) ) )
[Net Budget Sales] =
[Gross Budget Sales]
* ( 1 - MIN ( 1, MAX ( 0, [Discount Rate] ) ) )Step 1: define and save the shared function
DEFINE
FUNCTION NetAmountAfterDiscount = (
grossAmount : NUMERIC,
discountRate : NUMERIC
) =>
grossAmount * ( 1 - MIN ( 1, MAX ( 0, discountRate ) ) )
EVALUATE
{ NetAmountAfterDiscount ( 100, 0.1 ) }Step 2: both measures call that same UDF
[Net Sales] =
NetAmountAfterDiscount ( [Gross Sales], [Discount Rate] )
[Net Budget Sales] =
NetAmountAfterDiscount ( [Gross Budget Sales], [Discount Rate] )Both measure formulas call NetAmountAfterDiscount. The discount rule lives in one function, so you update it once. This reduces duplicated code; it does not promise faster query runtime.
Example assumes existing measures [Gross Sales], [Gross Budget Sales], and [Discount Rate]. Discount Rate is a decimal fraction (0.10 means 10%). The 0–100% clamp is an illustrative policy; use the business rule approved for your model.
Microsoft documents model compatibility level 1702 or higher. Check your model and Power BI version before using UDFs.
Timeline: Microsoft introduced DAX UDFs in preview in September 2025, so they were already in preview by November. Microsoft documents general availability beginning with the June 2026 release.
Microsoft sources
The documentation covers function syntax, saving a function to the model, calling it from a measure, and current availability.
Frequently asked questions
What does BI stand for?
BI stands for business intelligence: the practices and tools used to turn organizational data into analysis, reports, and dashboards that support decisions.
How does BI Radar help after a BI course?
It helps learners keep skills current with monthly, source-backed updates and practical questions about what to adopt, test, or monitor. It complements rather than replaces a course.
Is BI Radar an official vendor release feed?
No. BI Radar is an independent editorial guide. It links to vendor documentation and distinguishes sourced facts from practical interpretation.
Does every update mean a feature is available to me?
No. Availability may be general, preview, announced, or rolling out. Check the stated status and verify it in your tenant, region, and license.
How should teams use BI Radar?
Use it to identify relevant changes, check the primary sources, and decide whether to adopt, test in a controlled environment, or monitor the change.
What products does BI Radar cover?
Coverage focuses on supported business intelligence and modern data platforms, including Power BI, Microsoft Fabric, Snowflake, Databricks, and other registered tools when relevant.