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    <title>DEV Community: PRUDENCE JEMUTAI</title>
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      <title>Understanding Joins in Power BI</title>
      <dc:creator>PRUDENCE JEMUTAI</dc:creator>
      <pubDate>Wed, 24 Jun 2026 13:25:36 +0000</pubDate>
      <link>https://dev.to/prudence_jemutai_9fbc2672/understanding-joins-in-power-bi-2nm</link>
      <guid>https://dev.to/prudence_jemutai_9fbc2672/understanding-joins-in-power-bi-2nm</guid>
      <description>

&lt;p&gt;Join is combining two tables based on matching column. In Power BI joins are done using merge queries. &lt;/p&gt;

&lt;p&gt;The most common join types in Power BI are Inner Join,&lt;br&gt;
 Left Outer Join, Right Outer Join, Full Outer Join, Left Anti Join, and Right Anti Join.&lt;/p&gt;

&lt;p&gt;An &lt;strong&gt;inner join&lt;/strong&gt; returns only the records that have matching values in both tables. It is useful when you only want data that exists in both datasets.&lt;/p&gt;

&lt;p&gt;An &lt;strong&gt;Outer Join&lt;/strong&gt; returns records even when there is no matching value in the other table. Unlike an Inner Join, which only keeps matching records, an Outer Join preserves unmatched records and fills missing values with nulls.&lt;/p&gt;

&lt;p&gt;Outer Join = Keep unmatched records.&lt;br&gt;
Inner Join = Keep only matching records.&lt;/p&gt;

&lt;h2&gt;
  
  
  There are three types of Outer Joins
&lt;/h2&gt;

&lt;p&gt;1 &lt;strong&gt;Left outer join&lt;/strong&gt; – Returns all records from the left table and matching records from the right table.&lt;br&gt;
2 &lt;strong&gt;Right Outer Join&lt;/strong&gt; – Returns all records from the right table and matching records from the left table.&lt;br&gt;
3 &lt;strong&gt;Full Outer Join&lt;/strong&gt; – Returns all records from both tables, whether they match or not.&lt;/p&gt;

&lt;p&gt;A &lt;strong&gt;Left outer join&lt;/strong&gt; returns all records from the left table and only the matching records from the right table. If no match exists, the right-side columns contain null values. This join is commonly used when the left table contains the primary data that must be preserved.&lt;/p&gt;

&lt;p&gt;A &lt;strong&gt;Right outer join&lt;/strong&gt; works similarly but keeps all records from the right table and only matching records from the left table. Unmatched rows from the right table are retained with null values from the left table.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;A *Full Outer Join&lt;/strong&gt;* returns all records from both tables. When a matching value exists in both tables, the records are combined. If a record exists in only one table, it is still included, and the columns from the other table contain null values.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;An Anti Join&lt;/strong&gt; returns only the records that do not have a match in another table. It is commonly used to find missing or unmatched records&lt;/p&gt;

&lt;h2&gt;
  
  
  There are two types of Anti Joins
&lt;/h2&gt;

&lt;p&gt;A &lt;strong&gt;Left Anti Join&lt;/strong&gt; returns only the rows from the left table that do not have a matching record in the right table. It is useful for identifying missing transactions, unsold products, or customers without orders. (Think of it as "show me records in Table A(left) that missing in Table B(right)").&lt;/p&gt;

&lt;p&gt;A &lt;strong&gt;Right Anti Join&lt;/strong&gt; returns only the rows from the right table that do not have a matching record in the left table. This join is often used for data quality checks and finding orphan records.("show me records in Table B(right) that are missing in Table A(left)")&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Left Anti&lt;/strong&gt;   Records only in the left table&lt;br&gt;
&lt;strong&gt;Right Anti&lt;/strong&gt;  Records only in the right table&lt;/p&gt;

&lt;p&gt;In summary, joins are essential for data preparation and analysis in Power BI. Choosing the correct join type ensures accurate reporting and helps answer different business questions, from finding matching records to identifying missing or unmatched data.&lt;/p&gt;

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      <category>datascience</category>
      <category>analytics</category>
      <category>data</category>
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