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Data Connections and Preparation Flashcards
Tableau Desktop Foundations Flashcards
| 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. |
This deck focuses on understanding data connections, joins, unions, data blending, and basic techniques for data preparation.