Data Connections and Preparation Flashcards

Which of the following data sources can Tableau connect to directly?

Answer: Excel, SQL databases, and cloud services like Google Sheets

Tableau is designed to be a highly versatile data visualization tool, capable of connecting to a wide array of data sources. This includes common file types like Excel, robust database systems such as SQL databases, and modern cloud-based platforms like Google Sheets. This broad connectivity provides users with the flexibility to work with their data regardless of where it resides.

When would you use data blending instead of joins in Tableau?

Answer: When the data sources are from different servers

Data blending is primarily used when you need to combine data from different, independent data sources that cannot be joined directly at the database level. This often occurs when data resides on separate servers or comes from different types of databases. Joins, in contrast, are typically performed within a single data source or across sources that can be linked directly.

What is the primary advantage of using a data extract instead of a live connection?

Answer: Data extracts allow offline analysis and improve performance

A data extract creates a static snapshot of the data, which is stored locally and optimized for performance within Tableau. This allows for significantly faster query execution and the ability to work offline without a constant connection to the original data source. Unlike a live connection, extracts improve performance by pre-processing and storing the data efficiently.

You have two datasets that need to be joined: a list of customer orders and a list of customer information. Which join type should you use if you want all orders to be included, even those without matching customer information?

Answer: Left Join

A Left Join includes all rows from the 'left' table (customer orders in this scenario) and only the matching rows from the 'right' table (customer information). If an order doesn't have corresponding customer information, it will still be included in the result, with null values for the customer information fields. This fulfills the requirement to include all orders.

When connecting to a large dataset in Tableau, which option can help optimize performance?

Answer: Use a data extract with a filtered subset of the data

Connecting to a large dataset can significantly impact Tableau's performance. Using a data extract pre-processes and optimizes the data for Tableau, and filtering it to include only the necessary subset drastically reduces the volume of data being processed. This combination leads to much faster loading times and improved interactivity compared to a live connection to the full dataset.