Sort Ascending

Remove Duplicates

Group By

Filter Rows

Missing values can be identified by sorting the dataset in ascending order.

You can only handle missing values by ignoring them in your analysis.

You can identify missing values in Power Query by checking for nulls or blanks in columns, and handle them by removing rows or replacing them with specific values.

Identifying missing values requires using Excel formulas instead of Power Query.

Table.ChangeDataType

Column.TypeTransform

Table.Transform. data type

DataType.Convert

Delete all rows except the first one.

Use the sort function to arrange the data alphabetically.

Use the filter icon in the column header to select specific values or conditions.

Export the data to Excel and filter there.

Merging stacks tables by adding rows; appending combines based on a common column.

Merging adds new columns; appending removes duplicates.

Merging creates a new table; appending modifies the existing table.

Merging combines tables based on a common column; appending stacks tables by adding rows.

Replace Values

Group By

Sort Ascending

Remove Duplicates

It adds new entries to the dataset for completeness.

It formats data into a more readable structure.

It ensures data accuracy by eliminating redundant entries.

It increases data redundancy for better analysis.

Select the text column, go to 'Transform' > 'Data Type' > 'Date'.

Select the text column, go to 'Transform' > 'Format' > 'Date'.

Right-click the column and choose 'Convert to Number'.

Select the text column, go to 'Home' > 'Data Type' > 'Text'.

Sort the data in ascending order.

Group the rows by a different column.

Use the filter icon in the column header to apply a specific condition.

Delete the entire column with the condition.

Use 'Group By' to merge data from two queries.

Use 'Append Queries' to stack two queries vertically.

Use 'Merge Queries' in Power Query to combine two queries based on a common column.

Combine queries using a pivot table in Power Query.

The impact includes biased results, reduced accuracy, and potential errors in analysis.

Increased data size without any effect

No impact on data analysis

Improved accuracy in predictions

Transform Data

Load Data

Filter Data

Preview Data

Use 'Remove Other Columns' or 'Remove Columns' in Power Query.

Use 'Group By' to summarize data.

Use 'Add Column' to create new columns.

Use 'Sort' to rearrange the dataset.

The 'Group By' feature visualizes data trends through graphs.

The 'Group By' feature filters out irrelevant data without aggregation.

The 'Group By' feature aggregates data, helping to summarize and clean datasets by consolidating duplicates and calculating statistics.

The 'Group By' feature is used to sort data in ascending order.