Naming conventions in Power BI - Dashboard Guide

Dashboard Mode - Naming conventions

Dashboard Goal

Help users understand and apply clear naming rules for measures, columns, and tables in Power BI to keep reports easy to read and maintain.

Sample Data

OrderID	CustomerName	OrderDate	SalesAmount	Region
1001	Anna Smith	2024-01-10	250	North
1002	John Doe	2024-01-15	450	South
1003	Mary Johnson	2024-02-05	300	East
1004	James Brown	2024-02-20	150	West
1005	Linda Davis	2024-03-01	500	North

Dashboard Components

• KPI Card: TotalSales
  Formula: TotalSales = SUM('Sales'[SalesAmount])
  Shows total sales amount from all orders.
• KPI Card: AvgSalesPerOrder
  Formula: AvgSalesPerOrder = AVERAGE('Sales'[SalesAmount])
  Shows average sales amount per order.
• Table: Sales by Region
  Columns: Region, TotalSales
  Formula for TotalSales: TotalSales = SUM('Sales'[SalesAmount])
  Grouped by Region.
• Bar Chart: Sales by Region
  Visualizes total sales for each region.
• Text Box: Naming Convention Rules
  Explains naming rules:
  • Use PascalCase for measure names (e.g., TotalSales)
  • Use descriptive names for columns and tables
  • Prefix measures with their calculation type (e.g., Total, Avg)
  • Avoid spaces and special characters

Dashboard Layout

+----------------------+----------------------+
|      TotalSales      |   AvgSalesPerOrder   |
|       (KPI Card)     |       (KPI Card)     |
+----------------------+----------------------+
|                                              |
|          Sales by Region (Bar Chart)          |
|                                              |
+----------------------+----------------------+
|           Sales by Region (Table)             |
+----------------------+----------------------+
|           Naming Convention Rules (Text)     |
+----------------------------------------------+

Interactivity

Adding a slicer for Region filters the bar chart and the sales by region table. The KPI cards update to show totals and averages only for the selected region(s). The naming convention text box remains static as it explains rules.

Self Check

If you add a filter for Region = North, which components update?

• The TotalSales and AvgSalesPerOrder KPI cards update to show sales only for the North region.
• The Sales by Region bar chart and table update to show data only for the North region.
• The Naming Convention Rules text box does not change.

Key Result

A Power BI dashboard demonstrating clear naming conventions with KPIs, charts, and tables using sample sales data.

Practice

1. Why is it important to use clear and descriptive names for measures and columns in Power BI?

easy

A. It makes reports easier to understand and maintain.

B. It reduces the file size of the Power BI report.

C. It automatically improves the report's performance.

D. It hides sensitive data from users.

Solution

1. Step 1: Understand the role of naming in reports

   Clear and descriptive names help users and developers quickly understand what each measure or column represents.

2. Step 2: Recognize the impact on maintenance

   Consistent naming reduces confusion and makes updating or fixing reports easier over time.

3. Final Answer:

   It makes reports easier to understand and maintain. -> Option A

4. Quick Check:

   Clear naming = easier maintenance [OK]

Hint: Good names = easy reading and fixing [OK]

Common Mistakes:

• Thinking naming affects file size
• Assuming naming improves performance
• Believing naming hides data

2. Which of the following is the correct way to name a measure in Power BI following common naming conventions?

easy

A. TotalSales

B. mTotalSales

C. Measure_TotalSales

D. SalesTotalMeasure

Solution

1. Step 1: Identify common prefixes for measures

   Many teams use a prefix like 'm' to indicate a measure, making it easy to spot in lists.

2. Step 2: Compare options

   mTotalSales uses 'm' prefix with a clear name, which is a common and recommended practice.

3. Final Answer:

   mTotalSales -> Option B

4. Quick Check:

   Prefix 'm' = measure [OK]

Hint: Use 'm' prefix for measures to spot them fast [OK]

Common Mistakes:

• Not using any prefix for measures
• Using long or unclear prefixes
• Mixing measure and column naming styles

3. Given the following naming convention: prefix 'c' for calculated columns and 'm' for measures, what is the correct classification of cProfitMargin?

medium

A. Measure

B. Table Name

C. Calculated Column

D. Filter

Solution

1. Step 1: Analyze the prefix in the name

   The prefix 'c' indicates a calculated column according to the given convention.

2. Step 2: Confirm the rest of the name

   'ProfitMargin' is the descriptive part, so the full name 'cProfitMargin' is a calculated column.

3. Final Answer:

   Calculated Column -> Option C

4. Quick Check:

   Prefix 'c' = calculated column [OK]

Hint: Prefix 'c' means calculated column [OK]

Common Mistakes:

• Confusing 'c' prefix with measure
• Thinking it is a table name
• Assuming it is a filter

4. You see a measure named TotalSales and a calculated column named calcTotalSales. What is the main issue with these names?

medium

A. They are too long and complex.

B. The names are too short and unclear.

C. They use reserved keywords in Power BI.

D. They do not use consistent prefixes to identify their types.

Solution

1. Step 1: Check naming consistency

   The measure has no prefix, while the calculated column uses 'calc' prefix, causing inconsistency.

2. Step 2: Understand impact of inconsistency

   Inconsistent prefixes make it harder to quickly identify item types and maintain the report.

3. Final Answer:

   They do not use consistent prefixes to identify their types. -> Option D

4. Quick Check:

   Consistent prefixes = easier identification [OK]

Hint: Use consistent prefixes for all measures and columns [OK]

Common Mistakes:

• Thinking name length is the main problem
• Assuming reserved keywords are used
• Believing complexity is the issue

5. You want to create a naming convention for a Power BI project that includes tables, calculated columns, and measures. Which of the following naming schemes best follows best practices?

hard

A. tblCustomer, cCustomerAge, mTotalSales

B. CustomerTable, CustomerAgeCalc, TotalSalesMeasure

C. Customer, CustomerAge, TotalSales

D. tCustomer, calcAge, measureSales

Solution

1. Step 1: Identify prefixes for each item type

   Best practice uses clear prefixes: 'tbl' for tables, 'c' for calculated columns, 'm' for measures.

2. Step 2: Evaluate each option

   tblCustomer, cCustomerAge, mTotalSales uses these standard prefixes consistently and clearly, making it easy to identify item types.

3. Final Answer:

   tblCustomer, cCustomerAge, mTotalSales -> Option A

4. Quick Check:

   Standard prefixes = clear naming [OK]

Hint: Use 'tbl', 'c', 'm' prefixes for tables, columns, measures [OK]

Common Mistakes:

• Using inconsistent or unclear prefixes
• Not using any prefixes
• Using overly long or confusing names