Understanding Data Cardinality | Power BI || Belayet Hossain

1. ?????????????????????????? ??????????????????????:

Data cardinality refers to the unique values in a column of a dataset.

In the list [2, 3, 5, 3, 7, 2], the unique values are [5, 7] because they occur only once in the list.

2. ?????????? ???? ??????????????????????:

???????? ??????????????????????: A column with many unique values.

??????????????: Social Security Numbers, Order IDs, Customer ID, Transaction ID

???????????? ???? ?????????? ????:

??????????????: High cardinality columns require more storage because each unique value is stored separately.

??????????????????????:Can lead to slower performance, especially in large datasets, as more resources are required to process the data.

??????????????????????????: High cardinality can complicate relationships between tables, particularly if not properly indexed.

?????? ??????????????????????: A column with few unique values.

??????????????: Gender (Male, Female), Yes/No flags, Active/Inactive Status.

???????????? ???? ?????????? ????:

??????????????: Low cardinality columns are more storage-efficient because fewer unique values are stored.

??????????????????????: Queries involving low cardinality columns tend to be faster due to less data needing to be processed.

??????????????????????????: Easier to manage and optimize, especially in star schema designs.

3. ?????????????????????? ?????? ??????????????????????????:

??????-????-???????? (??:*): Common in Power BI, where one table has unique values (high cardinality) that relate to many rows in another table.

Example: A product table (unique product IDs) related to a sales table (many sales per product).

????????-????-?????? (*:??): The inverse of one-to-many, used when a table with many rows relates to a table with unique values.

????????-????-???????? (:) : More complex and used in scenarios where neither table has unique values. It can introduce performance challenges and is usually avoided unless necessary.

4. ???????? ??????????????????

???????????????????? ??????????????????????:

Where possible, reduce cardinality by categorizing data or using surrogate keys.

Avoid unnecessary high cardinality columns in relationships to improve performance.

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Use appropriate cardinality in table relationships to optimize query performance and data model size.

Leverage Power BI's relationship detection features but manually adjust cardinality settings as needed.

5. ?????????? ?????? ????????????????:

?????????????????????? ??????????????????: Power BI automatically detects cardinality when you create relationships, but it’s essential to review and adjust as necessary.

?????? ??????????????????: Certain DAX functions can be used to analyze and optimize cardinality, like ?????????????????????????? for counting unique values.

Understanding cardinality is crucial for optimizing relationships between tables and improving performance.