Clean, transform, and load data in Power BI

Question 1

Why is data cleaning important in Power BI?

Answer 1

To ensure the accuracy and reliability of data, making it ready for analysis and reporting.

Question 2

What is the first step in the data cleaning process in Power BI?

Answer 2

Profiling the data to understand its structure and quality.

Question 3

What tool is commonly used for data cleaning in Power BI?

Answer 3

Power Query Editor.

Question 4

What are some common data cleaning tasks in Power BI?

Answer 4

Removing duplicates, handling missing values, and correcting data types.

Question 5

What is the primary purpose of shaping data in Power BI?

Answer 5

To transform and refine raw data into a structured format suitable for analysis.

Question 6

What are some common data shaping tasks in Power BI?

Answer 6

Filtering rows, removing columns, grouping data, and creating calculated columns.

Question 7

Which tool in Power BI is used for shaping data?

Answer 7

Power Query Editor.

Question 8

How can you ensure data quality during the shaping process?

Answer 8

By performing data validation checks and applying consistent data transformation rules.

Question 9

What is the process of grouping data in Power BI?

Answer 9

Grouping data involves aggregating data based on specific criteria to summarize and analyze it more effectively.

Question 10

How can you pivot data in Power BI?

Answer 10

Use the “Pivot Column” feature in Power Query Editor to transform rows into columns based on a key field.

Question 11

What is the role of the “Unpivot Columns” feature?

Answer 11

It transforms columns into rows, making it easier to analyze data that was previously spread across multiple columns.

Question 12

What is a calculated column in Power BI?

Answer 12

A column created using DAX expressions to perform calculations on existing data within the model.

Question 13

Why might you want to rename queries in Power BI?

Answer 13

To make query names more obvious and user-friendly, improving clarity and usability.

Question 14

How can you replace null values in Power Query Editor?

Answer 14

By selecting the column, clicking Replace Values, entering null in the Value to Find box, and the replacement value (e.g., zero).

Question 15

Why is it important to remove duplicate values from columns in Power BI?

Answer 15

To ensure data accuracy and uniqueness, which can improve data analysis and reporting.

Question 16

Why is setting the correct data type important in Power BI?

Answer 16

Ensures data accuracy and optimizes performance in calculations and visualizations.

Question 17

What are common data types you might set in Power BI?

Answer 17

Text, Date, Whole Number, Decimal Number, and Boolean.

Question 18

How can data type mismatches affect Power BI reports?

Answer 18

They can lead to errors in calculations, incorrect aggregations, and issues in data visualizations.

Question 19

Why would you want to combine tables in Power BI?

Answer 19

To simplify the model by reducing the number of tables, handle tables with similar roles, merge tables with few columns into another, or use columns from different tables in a custom column.

Question 20

What are the two methods to combine tables in Power BI?

Answer 20

Merging and appending.

Question 21

What is appending queries in Power BI?

Answer 21

Adding rows from one table to another, resulting in a combined table with more rows.

Question 22

How do you append queries in Power BI?

Answer 22

Use the “Append Queries” option in Power Query Editor, selecting either “Append Queries” or “Append Queries as New” to create a new table.

Question 23

What must be consistent when appending tables in Power BI?

Answer 23

The column headers and data types should be the same across all tables being appended.

Question 24

What is merging queries in Power BI?

Answer 24

Combining columns from multiple tables into one based on a common column, similar to SQL JOIN operations.

Question 25

What is a key requirement for merging tables?

Answer 25

A common column, or key, that exists in both tables to align the data correctly.

Question 26

What are the join types available in Power BI when merging tables?

Answer 26

Left Outer, Full Outer, and Inner joins.

Question 27

Describe a Left Outer join in Power BI.

Answer 27

It displays all rows from the first table and only the matching rows from the second table.

Question 28

Describe a Full Outer join in Power BI.

Answer 28

It displays all rows from both tables, combining data where possible.

Question 29

Describe an Inner join in Power BI.

Answer 29

It displays only the rows that have matching values in both tables.

Question 30

What should you do before combining tables in Power BI?

Answer 30

Remove any unnecessary columns to streamline the resulting combined table.

Question 31

What is the purpose of profiling data in Power BI?

Answer 31

To study the nuances of data, determine anomalies, examine underlying data structures, and query data statistics like row counts and value distributions.

Question 32

What should you do before examining data in Power Query Editor?

Answer 32

Learn about the underlying data structures, viewable under the Model tab in Power BI Desktop.

Question 33

What can you do under the Model tab in Power BI Desktop?

Answer 33

Edit column and table properties, transform data using the Transform Data button, and manage relationships between tables.

Question 34

What feature in Power Query Editor helps identify data anomalies?

Answer 34

The Column Distribution feature under the View tab in the ribbon.

Question 35

What does the Column Quality feature show?

Answer 35

Percentages of data that is valid, in error, and empty.

Question 36

What is the significance of Column Distribution in Power Query Editor?

Answer 36

It shows the distribution of data within a column and the counts of distinct and unique values.

Question 37

What detailed statistics does the Column Profile provide?

Answer 37

Row counts, outliers, empty rows, minimum and maximum values, and value distribution.

Question 38

How can you change the default behavior of profiling only the first 1000 rows?

Answer 38

Select the profiling status in the status bar and choose "Column profiling based on entire data set."

Question 39

What additional statistics are provided for numeric columns in Column Statistics?

Answer 39

Count of zeroes, null values, average value, standard deviation, and counts of even and odd values.

Question 40

What is the purpose of the Advanced Editor in Power BI?

Answer 40

To view and directly modify the M code that Power Query uses to shape data.

Question 41

How do you access the Advanced Editor in Power Query?

Answer 41

By selecting the View ribbon and then clicking on Advanced Editor.

Question 42

What does each step in Power Query roughly correspond to in the Advanced Editor?

Answer 42

Each step corresponds to one or two lines of M code.

Question 43

Is it necessary to write M code to use Power Query?

Answer 43

No, it is not required, as most steps can be created using the graphical interface.

Question 44

How is M code written and structured?

Answer 44

M code is written top-down, where later steps can refer to previous steps by the variable name to the left of the equal sign.

Question 45

What should you be careful about when reordering steps in M code?

Answer 45

Reordering steps can ruin the statement dependencies, which can break the data transformation process.

Question 46

What is the 'in' statement used for in M code?

Answer 46

It is used to define the final data set result, typically referring to the last query step.

Question 47

How can the Advanced Editor be useful for customization?

Answer 47

It allows for modifications such as changing the name of a database directly in the code.

Question 48

What should you understand about each Power Query step created via the UI?

Answer 48

Each step is converted into M code, which can be read and modified in the Advanced Editor.