PREPARING DATA FOR TABLEAU

METHODS TO PREPARE DATA FOR TABLEAU

Tableau tools:

It is important to format data before it can be analyzed using Tableau; this helps to save time and prevent errors.

Tableau offers the following tools to help prep data for analysis:

DATA JOINS:

• A dataset is typically made up of a collection of tables related by specific fields or columns.

• The Joining method is used to combine the related data in those common fields.

• A Join results in a virtual table that is typically extended horizontally by adding columns.

Example:

Shown here is the analysis of data on product sales with two files:

The product ID field serves as the primary key to join the data from the two sets.

TYPES OF JOINS:

JOIN FROM DATA BASE:

Tableau facilitates creating joins in two ways:

1. Single database join: Joining tables from the same database requires only a single connection in the data source.

2. Cross database join:

· Cross-database Joins require setting up a multi-connection data source by creating a new connection to each database.

· Multi-connection data sources are helpful when different internal systems are used.

DATA BLENDING:

· Blending is a method of combining related data from multiple sources in a single view in order to analyze it.

· There is always one primary data source, while the rest become secondary data sources.

SPLITS:

Splitting data from one field into multiple columns is used often in data preparation.

AUTOMATIC SPLITS:

• A string field can be split automatically based on a common separator that Tableau detects (space or underscore).

• This split can be used to automatically separate a field’s value into a maximum of ten new fields, depending on the type of data connection.

CUSTOM SPLITS:

The custom split can also separate a string field into a maximum of ten new fields based on a separator within the original field.

You can choose to split the values at:

· The first n occurrences of the separator

· The last n occurrences of the separator

· All the occurrences of the separator

METADATA GRID:

· When preparing data for analysis, a list of fields is sometimes more useful than the data preview.

· The Metadata Grid view in Tableau allows you to quickly perform actions, such as rename, hide, and others, on multiple fields with a single command.

PIVOT:

Data is often not organized as a typical data set: field names along the columns and members along the rows.

The Pivot function in Tableau allows you to select the columns you want to manipulate and format them into a typical data set ready for analysis.

UNION:

· Data often also resides in multiple, separate files and may need to be combined into a “master file.”

· Tableau’s “Union” feature helps you assemble data from multiple small files into one large file.

DATA INTERPRETER:

This function automatically “cleans” your data and preps it for analysis.

Examples of items that need to be cleaned prior to analysis:

· Merged cells

· Titles

· Footnotes

· Blank rows or columns

CONCLUSION:

Tableau Prep Builder provides a modern approach to data preparation, making it easier and faster to combine, shape, and clean data for analysis within Tableau. By providing a visual and direct path to prep your data, you can get your hands on quality data in just a few clicks.