Merging Queries MCQS
Q. What does Merge Queries do in Power BI?
Solution:
Merge Queries joins two tables side-by-side on a shared key column, adding columns from the second table to the first — similar to a SQL JOIN.
Q. Which join kind keeps ALL rows from the first (left) table and only matched rows from the second?
Solution:
A Left Outer join retains every row from the left table and appends matching data from the right table; unmatched right-side cells show null.
Q. Where do you perform Merge Queries in Power BI?
Solution:
Merge Queries is a Power Query Editor feature found under Home → Merge Queries. It operates on queries before data is loaded into the model.
Q. What happens if the key columns in a merge have different data types (e.g., text vs. number)?
Solution:
Power Query does not auto-convert types during a merge. If one key is text ‘001’ and the other is number 1, no rows will match — you must align data types first.
Q. How is 'Merge Columns' different from 'Merge Queries'?
Solution:
Merge Columns concatenates two or more text columns in the same table using a separator. Merge Queries joins two separate tables based on a matching key.
Q. What is the most likely cause of a row count explosion after a Merge Queries step?
Solution:
When both tables have duplicate values in the key column, every combination is produced (a Cartesian product for those keys), multiplying the row count unexpectedly.
Q. In Power Query M code, which function is generated when you perform a Merge Queries operation?
Solution:
 The M function behind Merge Queries is Table.NestedJoin, which produces a nested table column that you then expand with Table.ExpandTableColumn.
Q. Which SQL operation is Append Queries equivalent to?
Solution:
Append Queries stacks rows from multiple tables, matching columns by name — this is equivalent to SQL UNION ALL.
Q. Where do you find Append Queries in Power BI?
Solution:
Append Queries is a Power Query Editor feature located on the Home tab, used during the data transformation stage before loading.
Q. What is the difference between 'Append Queries' and 'Append Queries as New'?
Solution:
‘Append Queries’ adds rows to the currently selected query. ‘Append Queries as New’ leaves both originals unchanged and creates a third, combined query.
Q. You need to append 12 monthly CSV files from a folder. What is the most efficient approach?
Solution:
Get Data → Folder loads all matching files from a directory and provides a Combine option to automatically append identically structured files — far more efficient than manual appending
Q. What M function does Power Query generate for an Append Queries step?
Solution:
The M function behind Append Queries is Table.Combine, which takes a list of tables and stacks their rows.
Q. Where do you find the Unpivot option in Power BI?
Solution:
Unpivot is a Power Query transformation found on the Transform tab in Power Query Editor.
Q. What is the difference between 'Unpivot Columns' and 'Unpivot Other Columns'?
Solution:
Unpivot Other Columns keeps your selected columns fixed and dynamically unpivots all other columns — better for sources that may gain new columns over time.
Q. Why is 'Unpivot Other Columns' generally preferred over 'Unpivot Columns'?
Solution:
 Unpivot Other Columns dynamically unpivots everything except your fixed selections, so when a new column appears in the source (e.g., a new month), it is automatically included.
Q. What is the M function generated by the Unpivot Other Columns step?
Solution:
The M function is Table.UnpivotOtherColumns, which takes the table, a list of columns to keep, and the names for the new Attribute and Value columns.
Q. What is the opposite of Unpivot in Power BI?
Solution:
Pivot is the reverse of Unpivot — it turns distinct row values into column headers, converting tall data back into a wide crosstab format.
Q. Where can you view the M code for a query?
Solution:
The Advanced Editor in Power Query Editor shows the complete M code for the selected query, structured as a let…in expression.
Q. What is the basic structure of every M query?
Solution:
Every M query uses a let…in structure: the let block defines named transformation steps, and the in clause returns the final result.
Q. M is case-sensitive. Which of the following is correct?
Solution:
M is case-sensitive — both function names and step names must match exact casing. Table.SelectRows is the correct form.
Q. Where do you create a parameter in Power BI?
Solution:
Parameters are created in Power Query Editor via Home → Manage Parameters → New Parameter.
Q. What types can a Power Query parameter have?
Solution:
Parameters support several types including Text, Decimal Number, Whole Number, Date, Date/Time, Date/Time/Timezone, Duration, True/False, and Binary.
Q. How do you check if a step is folding?
Solution:
Right-click a step in Applied Steps. If ‘View Native Query’ is clickable, that step has successfully folded to the source
Q. Which data source type does NOT support query folding?
Solution:
Flat files like CSV and Excel do not support a native query language, so Power Query cannot fold steps against them.
Q. Which step is most likely to break query folding?
Solution:
Custom columns using M expressions are often too complex for the connector to translate to SQL, breaking folding at that point.
Q. Why is query folding important for incremental refresh?
Solution:
Power BI’s incremental refresh partitions data by date range and sends each partition as a parameterized query to the server — this only works if the date filter folds.
Q. Query folding translates Power Query steps into which of the following?
Solution:
Folded steps are translated into native source queries — most commonly SQL SELECT statements with WHERE, GROUP BY, and JOIN clauses.
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