Top Tweets for #SQLBI
Going to be a good weekend read : )
Understanding Visual Calculations in DAX - SQLBI https://t.co/o20lqNHhuF #SQLBI
Back to the basics with DAX/Power BI : )
How CALCULATE works in DAX - SQLBI https://t.co/qmmsXcS6qa #SQLBI
Very important to learn different patterns for DAX! Also, gives you ideas of how to think about the businesses you support : )
Dynamic Pareto analysis in Power BI - SQLBI https://t.co/9A5nZ4moFy #SQLBI
Friday reading: ) let's improve DAX query writing!
Writing DAX Queries - SQLBI https://t.co/Pd41RSU5VO #SQLBI
If you want to get better at Power BI/DAX I highly recommend reading one article from SQLBI every day. Consistency pays off folks : )
Understanding how DAX evaluates IF statements - SQLBI https://t.co/JRHaRWwFkS #SQLBI
Learn from the best : ) Very good article on how to structure your DAX to return the top n products.
https://t.co/nrN6vswMmq #SQLBI
Using RANK instead of RANKX in DAX - SQLBI https://t.co/ow7GCFLX0L #SQLBI
Introducing calendar-based time intelligence in DAX - SQLBI https://t.co/y0Lcy3SFGJ #SQLBI
AnalyticsClaw #sqlbi
Introducing AI and agentic development for Power BI - SQLBI https://t.co/u1U4mc1vyk #SQLBI
Creating a Date Table manually in Power BI is a time sink. Writing DAX for YTD/YoY shouldn't take all day.
Bravo for Power BI fixes this:
✅ Auto-generates a professional Date table
✅ Adds 40+ Time Intel measures
✅ Optimizes model size
Work smarter. #PowerBI #DataFam #SQLBI
Hi #datafam found this helpful with data modeling on PowerBI.
Data modeling is the process of structuring data into related tables so analysis is accurate, fast and easy.
It is simply deciding how tables connect, what each table represents, and how data should flow so you can answer business questions correctly.
Best Practices
1. Follow the Star Schema
Use Fact tables (transactions, numeric values).
Use Dimension tables (lookup tables like Date, Customer, Product).
Avoid snowflake unless necessary.
👉 Improves performance, simplifies DAX, reduces ambiguity.
2. Create a Proper Date Table
A single, continuous Date table.
Mark as Date Table in Power BI.
Include fields: Year, Month, Quarter, Week, MonthName, YearMonth, etc.
👉 Critical for time intelligence (YTD, MTD, YoY).
3. Use Correct Relationship Directions
Use Single direction (one-way) relationships.
Avoid bi-directional filters unless truly needed.
Eg, One Date table connects to all facts via one-to-many.
👉 Prevents circular dependencies and performance issues.
4. Clean and Transform Data in Power Query, Not in DAX
Remove nulls
Correct data types
Split/merge columns
Standardize values
👉 Keeps the model fast and manageable.
5. Assign Correct Data Types and Formats
Dates must be Date type.
IDs should be Text, not numbers.
Numeric values must be Whole/Decimal Number.
👉 Wrong types cause inaccurate visuals and relationships.
6. Use Surrogate Keys Instead of Natural Keys
Create simple integer keys for joining tables.
Don’t use names, emails, or long text as keys.
👉 Improves join speed and reduces errors.
7. Reduce Cardinality
Fewer unique values = better performance.
Avoid using columns with many distinct values in relationships.
Reduce precision where possible.
👉 Smaller model = faster DAX.
8. Organize Facts and Dimensions Clearly
Examples:
✔ Fact Tables:
Sales
Orders
Shipments
Payments
✔ Dimension Tables:
Date
Customer
Product
Supplier
Geography
👉 Helps maintain a clean star structure.
9. Avoid Many-to-Many Relationships
They slow down models.
Can create ambiguous results.
When needed → use a bridge table.
👉 Keeps relationships clear and predictable.
10. Create Explicit Measures
Avoid using implicit "Auto Sum".
Write measures using DAX: SUM, CALCULATE, DIVIDE, etc.
Use a dedicated Measures Table.
👉 Makes the model easy to maintain.
11. Use Friendly Column and Table Names
Use names people understand.
Avoid abbreviations like “CustID” → “Customer ID”.
Avoid spaces-at-end or weird characters.
12. Remove Unnecessary Columns and Tables
Delete unused fields after building visuals.
Disable “Load to Model” for staging tables.
👉 Reduces dataset size and boosts refresh speed.
13. Enable Data Validation Rules
Check duplicates in dimension keys.
Ensure no missing foreign keys in fact tables.
👉 Ensures data integrity.
14. Document Your Model
Add descriptions to:
Measures
Columns
Tables
👉 Helps others understand your model easily.
AI and Agentic Development for Power BI - SQLBI https://t.co/MWEytQTpsX #SQLBI
Newsletter #300 is a significant milestone for SQLBI.
I thought this was a good time to clarify SQLBI’s position on a topic we haven't discussed much yet: Artificial Intelligence (AI).
https://t.co/74kWAAxgNl
#newsletter #sqlbi #ai
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🔁 Retweet to upgrade your BI circle
#PowerBI #DAX #DataModeling #SQLBI #DataAnalytics #FreeLearning #BItools
Tools in Power BI - via SQLBI https://t.co/cF1R7Oe9yj #SQLBI
新しい DAX タイム インテリジェンス関数の追加とか、Power BI デスクトップでのDirect Lakeモデルの作成とか、楽しみな発表が多かったですね。
#PBIJP #SQLBI
————
Fabric Conference 2025 での DAX とセマンティック モデルの発表の要約:
1. Direct Lake とインポート モード:
- Direct Lake の 2 つのフレーバー: SQL エンドポイント上の Direct Lake と OneLake の Direct Lake。
- Power BI Desktop での Direct Lake モデルの作成。
- Direct Lake モードとインポート モードの複合モデル。
- Lakehouse の具体化されたビュー。
- Direct Lake の計算テーブルと計算列。
2. DAX のカレンダー:
- Date テーブルに基づく複数のカレンダーの導入。
- 新しい DAX タイム インテリジェンス関数の追加。
3. DAX のユーザー定義関数 (UDF):
- DAX で定義された関数の記述と使用。
- DAX UDF の構文と例。
Always felt that there has to be some scenarios where using pie charts would not be...ahem..,the end of the world!!!
Great post from @kurtbuhler on SQLBI. Especially loved his take on not using rules of "how" to replace an understanding of "why"!!
https://t.co/PuhTRaBXzf #SQLBI
Using pie charts is not the end of the world - SQLBI https://t.co/PPM7rYS78b #SQLBI
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