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Data Preparation and Transformation Flashcards
Microsoft Power BI Data Analyst Flashcards
Study our Data Preparation and Transformation flashcards for the Microsoft Power BI Data Analyst exam with 30+ flashcards. View as flashcards, a searchable table, or as a fun matching game.
| Front | Back |
| How are errors in Power Query handled? | Identify error cells and use "Replace Errors" or transformation steps to handle them. |
| How can you add a calculated column in Power Query? | Use the "Add Column" tab and define a formula with Power Query's M language. |
| How can you load transformed data into Power BI? | Click "Close & Load" to import data into the data model or worksheet. |
| How can you rename a column in Power Query? | Right-click the column header and select "Rename." |
| How can you replace missing values in a dataset? | Use the "Replace Values" or "Fill Down/Up" features in Power Query. |
| How do you apply data sorting in Power Query? | Use the "Sort Ascending" or "Sort Descending" options in the column menu. |
| How do you change the data type of a column in Power Query? | Use the "Data Type" dropdown menu in the column header. |
| How do you filter rows in Power Query? | Use the "Filter Rows" option to include or exclude specific values or ranges. |
| How do you remove duplicate rows in Power Query? | Use the "Remove Duplicates" feature under the "Home" tab. |
| What does "Group By" do in Power Query? | Aggregates data into groups based on specified columns. |
| What does "Keep Top Rows" do? | Keeps a specified number of rows from the top of a dataset. |
| What does "Remove Columns" do in Power Query? | Deletes selected columns from the dataset permanently. |
| What does the "Split Column" feature do? | It splits text data into multiple columns based on a delimiter. |
| What does the "Transpose" feature do? | Converts rows into columns and vice versa. |
| What file formats can Power Query connect to? | Excel, CSV, JSON, XML, and text files, among others. |
| What is "Fuzzy Matching" in Power Query? | A technique for merging or matching data with approximate matches. |
| What is a delimiter? | A character used to separate data fields, such as a comma, space, or tab. |
| What is a Power Query step? | A recorded action or transformation applied to the data in sequence. |
| What is a query parameter in Power Query? | A dynamic input that can be used to filter or modify data queries. |
| What is the "Conditional Column" feature used for? | Creates a column based on conditional logic or rules. |
| What is the "Merge Queries" function? | Combines two tables based on a common column (key). |
| What is the "Pivot Column" feature used for? | Transforms rows into columns based on a specific value. |
| What is the "Reference" function in Power Query? | Creates a new query based on an existing one without altering the original. |
| What is the "Unpivot Columns" feature used for? | Converts columns into rows for more flexible data analysis. |
| What is the function of the "Append Queries" tool in Power Query? | It combines multiple tables or queries into a single table. |
| What is the importance of data preparation in analytics? | Ensures data quality, consistency, and accuracy before analysis. |
| What is the M language in Power Query? | The formula language used to create and edit query transformations. |
| What is the primary purpose of Power Query? | To clean, transform, and shape data before analysis. |
| What is the purpose of previewing data in Power Query? | To verify structure, detect issues, and ensure proper transformation steps. |
| Why should you document data transformation steps? | To ensure traceability and transparency for future review. |
About the Flashcards
Flashcards for the Microsoft Power BI Data Analyst exam focus on Power Query tools for cleaning, transforming, and shaping data before analysis. The cards test common operations such as removing duplicates, splitting columns by delimiters, replacing missing values, changing data types, and renaming or removing columns, plus practical steps like previewing data and documenting transformation steps.
Students can review query structure and M language basics, conditional columns, parameters, and functions for grouping, sorting, pivoting and unpivoting, appending or merging tables, fuzzy matching, and handling errors. Cards also reinforce how to load transformed data into Power BI or a worksheet and when to apply filters, Keep Top Rows, or calculated columns.
Topics covered in this flashcard deck:
- Data cleaning and shaping
- Pivot and unpivot
- Merge and append queries
- M language basics
- Error handling and types
- File connections and formats