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    <title>DEV Community: Bethuel Ngetich</title>
    <description>The latest articles on DEV Community by Bethuel Ngetich (@bethuel_ngetich_ea8b7b104).</description>
    <link>https://dev.to/bethuel_ngetich_ea8b7b104</link>
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      <title>DEV Community: Bethuel Ngetich</title>
      <link>https://dev.to/bethuel_ngetich_ea8b7b104</link>
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      <title>Why Is Your Power BI Dashboard So Slow? 🐌</title>
      <dc:creator>Bethuel Ngetich</dc:creator>
      <pubDate>Sun, 28 Jun 2026 15:48:28 +0000</pubDate>
      <link>https://dev.to/bethuel_ngetich_ea8b7b104/why-is-your-power-bi-dashboard-so-slow-12md</link>
      <guid>https://dev.to/bethuel_ngetich_ea8b7b104/why-is-your-power-bi-dashboard-so-slow-12md</guid>
      <description>&lt;p&gt;Have you ever opened a dashboard and it took forever for it to load?&lt;/p&gt;

&lt;p&gt;Before blaming Power BI, take a look at your data model.&lt;/p&gt;

&lt;p&gt;In most cases, a slow dashboard is the result of an inefficient data model, not the BI tool itself.&lt;/p&gt;

&lt;p&gt;But what exactly is a data model?&lt;/p&gt;

&lt;p&gt;A data model is the way your data is structured through relationships, schemas, and joins. A well-designed model makes your dashboards faster, easier to maintain, and more scalable.&lt;/p&gt;

&lt;p&gt;Here are the three core concepts every BI developer should master.&lt;/p&gt;

&lt;p&gt;Relationships 🔗&lt;/p&gt;

&lt;p&gt;Relationships define how tables connect with one another. The most common types are:&lt;/p&gt;

&lt;p&gt;One-to-One (1:1)&lt;br&gt;
One-to-Many (1) ✅ The preferred relationship in most BI scenarios.&lt;br&gt;
Many-to-Many (N) ⚠️ Use sparingly—they often introduce ambiguity and can negatively impact performance.&lt;/p&gt;

&lt;p&gt;Tip: Design relationships based on your business logic while following the best practices recommended by your BI tool. For example, Power BI performs best with a star schema built around 1 relationships.&lt;/p&gt;

&lt;p&gt;Schemas 📐&lt;/p&gt;

&lt;p&gt;The way you organize your tables has a significant impact on performance.&lt;/p&gt;

&lt;p&gt;⭐ Star Schema (Recommended)&lt;/p&gt;

&lt;p&gt;A Star Schema consists of:&lt;/p&gt;

&lt;p&gt;A central Fact Table that stores measurable business events (sales, orders, transactions, etc.).&lt;br&gt;
Multiple Dimension Tables that provide context (Date, Customer, Product, Region, etc.).&lt;/p&gt;

&lt;p&gt;This is the industry standard for analytics because it minimizes joins and delivers excellent query performance.&lt;/p&gt;

&lt;p&gt;❄️ Snowflake Schema&lt;/p&gt;

&lt;p&gt;A Snowflake Schema extends the Star Schema by normalizing dimension tables into additional related tables.&lt;/p&gt;

&lt;p&gt;Pros:&lt;/p&gt;

&lt;p&gt;Reduces data redundancy&lt;br&gt;
Easier to maintain standardized dimensions&lt;/p&gt;

&lt;p&gt;Cons:&lt;/p&gt;

&lt;p&gt;Requires more joins&lt;br&gt;
Can slow down analytical queries&lt;br&gt;
🌌 Galaxy Schema&lt;/p&gt;

&lt;p&gt;A Galaxy Schema (also known as a Fact Constellation) contains multiple fact tables that share common dimension tables.&lt;/p&gt;

&lt;p&gt;This approach is ideal for large enterprise data warehouses supporting multiple business processes.&lt;/p&gt;

&lt;p&gt;Joins 🧩&lt;/p&gt;

&lt;p&gt;Joins determine how data is combined during ingestion or transformation.&lt;/p&gt;

&lt;p&gt;Some of the most common join types include:&lt;/p&gt;

&lt;p&gt;INNER JOIN&lt;br&gt;
LEFT JOIN&lt;br&gt;
RIGHT JOIN&lt;br&gt;
FULL OUTER JOIN&lt;br&gt;
LEFT ANTI JOIN&lt;br&gt;
RIGHT ANTI JOIN&lt;/p&gt;

&lt;p&gt;Choosing the right join not only ensures accurate results but can also reduce unnecessary data processing.&lt;/p&gt;

&lt;p&gt;The Bottom Line&lt;/p&gt;

&lt;p&gt;Fast dashboards start with a well-designed data model.&lt;/p&gt;

&lt;p&gt;A good model combines:&lt;/p&gt;

&lt;p&gt;✅ Appropriate relationships&lt;br&gt;
✅ The right schema design&lt;br&gt;
✅ Efficient joins&lt;/p&gt;

&lt;p&gt;Investing time in modeling your data before building visuals will save you countless hours of troubleshooting and dramatically improve dashboard performance.&lt;/p&gt;

&lt;p&gt;💬 What schema do you use most often in your BI projects?&lt;/p&gt;

&lt;p&gt;Do you stick with the classic Star Schema, or have you found situations where Snowflake or Galaxy schemas work better?&lt;/p&gt;

&lt;p&gt;I'd love to hear your thoughts in the comments!&lt;/p&gt;

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      <category>analytics</category>
      <category>database</category>
      <category>microsoft</category>
      <category>performance</category>
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