Power BI

 1. What is Power BI and how have you used it in your projects?

Sample Answer:

Power BI is a powerful business analytics tool developed by Microsoft that allows users to visualize data, share insights, and make data-driven decisions. In my recent project, I used Power BI to analyze Bitcoin price trends. I connected it to multiple sources, including historical price data from APIs and sentiment data from Twitter. I performed data cleaning and transformations in Power Query, built custom measures using DAX, and created interactive dashboards to track trends, correlations, and sentiment-driven price movements.

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2. What are the different components of Power BI?

Sample Answer:

Power BI has several components:

• Power BI Desktop – where reports are created.

• Power BI Service – cloud-based platform for sharing and collaboration.

• Power BI Mobile – for accessing reports on mobile devices.

• Power Query – used for data ingestion and transformation.

• DAX (Data Analysis Expressions) – used for creating custom calculations.

• Power BI Gateway – connects on-premise data to Power BI Service.

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3. What is DAX? Give an example of a DAX formula you've used.

Sample Answer:

DAX stands for Data Analysis Expressions. It's a formula language used in Power BI for creating calculated columns, measures, and custom tables.
For example, in my Bitcoin project, I created a DAX measure to calculate the 7-day moving average of the Bitcoin price:

7DayMA = AVERAGEX(
    LASTN(7, ORDERBY(VALUES('Bitcoin'[Date]), 'Bitcoin'[Date], DESC)),
    CALCULATE(SUM('Bitcoin'[Close]))
)

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4. How do you optimize a slow Power BI report?

Sample Answer:

I follow several steps to optimize slow reports:

• Reduce the number of visuals on a page.

• Limit data loaded using filters or row-level security.

• Optimize DAX by avoiding complex row context transitions.

• Use summary tables instead of detailed tables.

• Disable auto date/time if not needed.

• Use performance analyzer to identify bottlenecks.

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5. What is the difference between a calculated column and a measure?

Sample Answer:

A calculated column is computed during data load and stored in the data model; it's useful when you need the value in rows, like creating categories or flags.
A measure is calculated on the fly, based on the filter context. It’s more efficient for aggregations like sums, averages, or KPIs.
In general, I prefer measures over calculated columns for performance.

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6. Can you explain row-level security (RLS)?

Sample Answer:

Row-level security (RLS) allows us to restrict access to data at the row level for different users. In Power BI, we define roles and DAX filters on tables. For example, in a sales dashboard, we can restrict each sales manager to view only their own region’s data by applying a filter like [Region] = USERNAME().

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7. How do you handle dynamic titles or measures based on slicer selections?

Sample Answer:

I use DAX measures and cards to create dynamic titles. For example:

SelectedProduct = 
"Sales Report for " & SELECTEDVALUE('Product'[ProductName], "All Products")

Then I place this measure in a card visual to reflect the current selection dynamically.

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Let me know your background or specific project, and I can tailor these answers even more for you.