Mastering Tableau 2018.1, Second Edition 3.1: Data Preparation and Cleaning Data Sources with Dates and Numbers

The video tutorial covers data cleaning and preparation for visualization in Tableau. It starts with the importance of clean data, followed by filtering data by date, extracting specific date parts, and formatting dates. The tutorial also explains number formatting and conversion, and handling null values by replacing them with zeros.

Why is it important to clean data before visualization?

• To increase data complexity

• To reduce file size

• To ensure accurate analysis

• To make it look pretty

What is the first step in preparing dates for analysis in Tableau?

• Convert dates to text

• Select only the required dates

• Select all available dates

• Ignore date formatting

How can you extract only the day part from a date in Tableau?

• Use the DATEPART function

• Use the DAY function

• Use the MONTH function

• Use the YEAR function

What is the purpose of converting dates to discrete format in Tableau?

• To remove all date values

• To display dates as continuous values

• To show each date as a separate value

• To merge all dates into one

Which function can be used to format dates in Tableau?

• FORMATDATE

• DATETRUNC

• DATEFORMAT

• DATEPART

What is the purpose of type conversion in number formatting?

• To convert decimals to integers

• To change the number format

• To change text to numbers

• To convert numbers to text

How can you handle null values in a dataset in Tableau?

• Convert them to text

• Delete the entire row

• Ignore them

• Replace them with zeros using the ZN function

What is the difference between number whole and number decimal in Tableau?

• Number whole is for integers, number decimal includes decimals

• Number whole includes decimals, number decimal does not

• Number whole is for dates, number decimal is for text

• Number whole is for text, number decimal is for numbers

Why is it important to format numbers correctly in Tableau?

• To make the data look colorful

• To ensure accurate calculations and analysis

• To reduce the size of the dataset

• To increase the complexity of the data

What happens if null values are not handled in a dataset?

• They are automatically converted to zeros

• They can cause errors in calculations

• They are ignored by Tableau

• They are converted to text