Imagine you have a BI dashboard that shows sales data. How does customizing this dashboard help you work faster?
Think about how focusing on relevant information saves time.
Customization allows users to tailor dashboards to their needs, showing only relevant data. This reduces clutter and speeds up decision-making.
You need to create a monthly sales report that updates automatically. Which customization feature helps you most?
Think about how automation can save time.
Automatic data refresh and filters ensure the report updates itself with current data, reducing manual work and speeding up reporting.
Given a sales table with columns: Date, Product, SalesAmount, which DAX measure calculates total sales only for the current year?
Total Sales Current Year = CALCULATE(SUM(Sales[SalesAmount]), YEAR(Sales[Date]) = YEAR(TODAY()))
Focus on filtering sales by the year matching today's year.
Option C correctly filters sales to only those where the year of the sale date equals the current year, summing those amounts.
You want to show monthly sales trends over a year with the ability to filter by product category. Which visualization is best?
Think about how trends and filtering work best together.
A line chart shows trends over time clearly, and slicers let users customize the view by product category, speeding up insights.
What error does this DAX measure cause?
Measure: Sales Last Month = CALCULATE(SUM(Sales[Amount]), PREVIOUSMONTH(Sales[Date]))
Sales Last Month = CALCULATE(SUM(Sales[Amount]), PREVIOUSMONTH(Sales[Date]))
Check if the date column is properly used with time intelligence functions.
PREVIOUSMONTH requires the date column to be from a proper date table marked as a date table. If Sales[Date] is not from a date table, it causes an error.
