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What is Tableau Prep? – Features, Uses, Workspace, & More

Tableau is a powerful data visualization tool that is mainly used in data analysis and business intelligence (BI) for better business decision-making. Users can create charts, graphs, maps, reports, and dashboards, which enable them to extract meaningful insights from huge volumes of data. Its data visualization capabilities enable professionals at any level of an organization to comprehend data outcomes. To enhance its data visualization capability even more, the Tableau Prep tool is used, which helps in data preparation before it gets interpreted for deriving visual results. 

Table of Contents

  • What is Tableau Prep?
  • Features of Tableau Prep
  • Uses of Tableau Prep
  • Tableau Prep Workspace
  • How Tableau Prep Stores the Data?
  • Conclusion

What is Tableau Prep?

Tableau Prep is a data preparation and ETL (extract, transform, and load) tool within the Tableau ecosystem. It is referred to as an ETL tool because it extracts data from different sources, transforms it into an appropriate format, and then loads it at a location for data analysis koiusa.

Data sets require a lot of cleaning before they are ready for visual analysis. This tool allows you to clean, organize, and combine data from multiple sources in a more streamlined manner. Professionals are updating there skills in tableau prep by referring to online tableau course or other resources available on the internet to make themselves eligible as per the industry standards.

Features of Tableau Prep

A variety of features in Tableau Prep are available to make the process of preparing data easier. These include:

  • Visual Data Preparedness: Tableau Prep offers a real-time data flow interface, allowing users to view transformations, remove unwanted columns, fix errors, and standardize formats. This enables quick identification of issues and the impact of changes on the data. 
  • Data Integration: Tableau Prep makes it simple to connect and combine data from different sources, such as databases, spreadsheets, and cloud applications.
  • Combining and Reshaping Data: Join, Union, Pivot, and Split operations are used to combine and reshape data sources. These operations enable the creation of data sources and columns in the most extensive and effective data set for use in data analysis. 
  • Drag-and-Drop Interface:  A big advantage of Tableau Prep is its user-friendly drag-and-drop interface. It allows users to complete challenging data preparation tasks without having to write any SQL code.
  • Intelligent Tips: Tableau Prep employs machine learning algorithms to offer suggestions and recommendations for data cleaning and transformation tasks, which saves time.
  • Data Profiling: Anomalies, inconsistencies, and missing values in the data can be found using the built-in data profiling tools that Tableau Prep provides detectmind
  • Connects to Other Tableau Tools: For additional analysis and visualization, prepared data can be easily exported to Tableau Desktop, Tableau Server, or Tableau Online.
  • Performs Calculations: With Tableau Prep, users can prepare their datasets for deeper analysis by adding calculations, aggregations, and conditional logic.

Uses of Tableau Prep

Some of the uses of Tableau Prep include wotpost:

  • Data Cleaning:  It involves consolidating, filtering, and removing duplicates and redundant information to reduce dataset size, ensure accuracy, and maintain consistency in analysis.
  • Data Structuring: It helps to structure the data by reshaping and organizing it in a way that makes it easier to visualize. It also transforms the data from a wide to a long format to identify patterns and insights. 
  • Data Blending: Tableau Prep allows data blending by combining data from different sources in a meaningful way to create a single and unified dataset.
  • Automates Cleaning Workflows: Tableau Prep’s Automate Flow streamlines data preparation, ensuring accuracy and consistency in cleaning workflows. Users can configure automated notifications for process failures, facilitating problem identification and resolution. 

Tableau Prep Workspace

The Tableau Prep workspace consists of the following:

  •  Connections Pane: It displays the databases and files and connects with the three coordinated panes to help you interact and explore your data. 
  • Flow Pane: This is where you begin to build the flow of cleaning, combining, and shaping the data. Steps are displayed in the Flow Pane as you connect to clean, shape, and merge the data. These steps appear in a manner that will tell you the type of operation that is carried out, the order in which it proceeds, and how it will impact your data. 
  • Profile Pane: This pane displays the structure of your data at any point along the flow. Depending on the operation you run or the step you choose in the Flow pane, your data’s structure is displayed in various ways.

For each step in your flow, this pane’s toolbar offers cleaning operations that you can use. There is an options menu where you can choose from the various operations you can run on the data.

A few examples are:

  • Search, Sort, and Split Fields
  • Filter, Include, or Exclude Values
  • Find and Fix Null Values
  • Rename Fields
  • Data Grid: It provides row-level information about your data. The operations specified in the Profile pane are reflected in the values shown in the Data grid. In this pane, you can perform the same cleaning operations on data as in the Profile Pane.

How Tableau Prep Stores the Data?

The Tableau Prep stores data as follows – 

  • Once you connect the data sources to Tableau Prep and begin the flow of operations, the frequently used data gets stored in the format of a .hyper file
  • This stored data then gets securely saved in a temporary file directory under the file name Prep BuilderXXXXX. Here, XXXXX is the UUID (universally unique identifier). 
  • This file is deleted once the flow has been saved. 


Tableau Prep is an excellent tool for data preparation and ETL (extract, transform, and load) actions on data sets. This feature within Tableau’s environment is a huge advancement to make the data analysis process cleaner and more efficient. 

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