5 Data Prep Tasks You Can Perform in Tableau Desktop
Updated: Sep 4, 2020
Tableau desktop is no doubt one of the leaders in business intelligence industry according to market research firm – Gartner. With an intuitive interface (drag and drop interface) and a host of features and capabilities for authoring dashboards.
Like other data visualization tools, Tableau relies on a well-structured data to create dashboards. This calls for the need of data preparation tools e.g. Tableau prep or availability of data preparation capabilities within Tableau desktop to help developers quickly shape data when need be.
Therefore in this article, we'll explore five data prep tasks you can perform in Tableau desktop.
Data preparation in Tableau desktop
Pivoting data is a technique of transposing data from a crosstab format into a columnar format for quick analysis.
Analyzing data stored in a crosstab format can be difficult, when one type of information is stored in multiple columns, pivoting the data from columns to rows makes the data much easier to work with.
For instance, in this sample data set on social media shows responses of different individuals on different social media channels they use. To quickly analyze this data, you will first need to shape it by pivoting. Pivoting the data will bundle all the social media channels in one column and the responses in another column hence simplifying your analysis.
Step by step guide on how to pivot data in Tableau desktop
Splitting fields into multiple fields
Sometimes data may contain multiple units of information in the same column. A good example is the first and last name of a customer in one column. In scenarios where you need to perform your analysis based on the customer’s first name, you can split or custom split such columns into multiple columns.
In the example below we split the ‘Customer Name’ column into multiple columns ‘First name’& ‘Last name’ respectively.
Changing data types
All fields in a data source have a data type. Data type reflects the kind of information stored in that field. And each data type is represented by a unique icon. Sometimes Tableau can misinterpret these data types in which case you can change the data type by clicking on the icon.
Grouping is applicable when you need to combine related members in a field. Grouping is useful for both correcting data errors (e.g. Combining Africa, Afrika & Afric into one data point) as well as answering ‘What if’ type of questions (e.g. What if we combine the east and west regions?)
In this example, grouping is used to combine ‘Africa’, ‘Afrika’ and ‘afric’ into a single data point named ‘Africa’.
Data interpreter lives within Tableau desktop. After connecting to data, if Tableau detects sub-tables in your data, you’ll be presented with the option to turn on data interpreter. The data interpreter will draw out sub-tables and exclude any extraneous information.
Connecting to this data Tableau will prompt you to turn-on the data interpreter.
Using the data interpreter excludes the irrelevant information.
These are some of simple data prep tasks you can perform in Tableau desktop.
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