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Data Connections and Preparation Flashcards
Tableau Desktop Foundations Flashcards
Study our Data Connections and Preparation flashcards for the Tableau Desktop Foundations exam with 20+ flashcards. View as flashcards, a searchable table, or as a fun matching game.
| Front | Back |
| Difference between a join and a union | A join combines data horizontally (columns), whereas a union combines data vertically (rows). |
| How can null values be handled | Null values can be replaced, removed, or filled with appropriate data depending on the context. |
| How does a cross-join work | A cross-join creates combinations of every row in one table with every row in another. |
| What are null values | Null values represent missing or undefined data in a dataset. |
| What is a data connection | A data connection is a way to link and access data from a source such as a database or file. |
| What is a full outer join | A full outer join includes all rows from both tables, with nulls for any unmatched rows. |
| What is a left join | A left join includes all rows from the left table and the matching rows from the right table. |
| What is a primary key in a table | A unique identifier for each row in a table. |
| What is a union in data preparation | A union combines rows from two or more datasets. |
| What is an inner join | An inner join includes only rows that have matching values in both tables. |
| What is data blending | Data blending combines data from disparate sources without requiring direct relationships in the database. |
| What is data deduplication | The process of identifying and removing duplicate records from a dataset. |
| What is data preparation | The process of cleaning, transforming, and structuring data for analysis. |
| What is filtering in data preparation | The process of selecting specific data based on defined criteria. |
| What is pivoting in data preparation | Pivoting restructures data from rows into columns or vice versa to make data analysis easier. |
| What is the benefit of a union | Unions combine data from multiple tables into a single dataset, making analysis more comprehensive. |
| What is the purpose of joining data | To combine columns from two or more tables based on a related field. |
| What should you do before joining two tables | Ensure they have a common field or relationship that can connect the data accurately. |
| When do you use data blending | Use data blending when data sources cannot be joined directly or are stored in different systems. |
| Why is data cleaning important | To remove errors, inconsistencies, and unnecessary information that can affect analysis. |
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About the Flashcards
Flashcards for the Tableau Desktop Foundations exam deliver a concise review of core data preparation skills tested on the certification. Students revisit how data connections work, what makes a reliable primary key, and the distinctions among joins, unions, and blends that integrate information from multiple sources.
The deck reinforces practical techniques for cleaning and reshaping data before analysis, from handling null values and deduplication to filtering and pivoting tables. Short definitions and comparisons help you recall when to use an inner join versus a full outer join, or why blending is preferable when datasets live in separate systems.
Topics covered in this flashcard deck:
- Data connections & keys
- Joins (inner, outer, cross)
- Unions & data blending
- Cleaning: nulls, deduplication
- Filtering & pivoting