Tableau recently promoted its Maestro beta program to a licensed data cleansing and modification tool called Prep. Tableau Prep comes bundled with Tableau Desktop in their new Creator license. The purpose of bundling the two products together is to speed up the time it takes to import clean data (and thereby speeding up the time to data analysis) by simplifying the data cleansing process.

Data School Cohort 17 presentsIn this webinar you’ll get familiar with Tableau Prep’s interface, how to connect to your data, and how to get your data cleane. Data Cleaning and Visualizations with Tableau Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod. Outputting the Data. After I was done with all the cleaning steps, I setup the Prep file to export the data. This gave me a Tableau Data Extract to import right into Tableau Desktop. Playing with the Data. Now let’s give the data a test. I went ahead and created a nice little map with the average star rating for facilities by zip code. Data can be generated, captured, and stored in a dizzying variety of structures, but when it comes to analysis, not all data formats are created equal. Data preparation is the process of cleaning dirty data, restructuring ill-formed data, and combining multiple sets of data for analysis. It involves transforming the data structure, like rows and columns, and cleaning up things like data types and values. In this video, we are going to discuss data cleaning and Tableau using a file that needs some work before it's ready for analysis. For this demonstration, we'll be using the Data Prep-Flights Excel file, which you can download from the course material. Our first step is to open the file in Excel.

A quick tip: With Tableau, sometimes the shininess of a new feature (or in this case, a whole new tool) can obscure the actual need for the functionality. If your dataset is already clean, or you have simple data cleanup needs (like renaming fields or changing data types) the legacy Tableau Data Source screen is still the fastest way for you to proceed. With that said, Tableau Prep does simplify much of the manual cleansing process that the legacy Data Source screen has available.

Tableau Prep’s Top Features:

  • Data Cleanup

This is why Tableau Prep exists. If you’ve used Tableau Desktop in the past and you wanted to clean your data, you either cleaned it in your source system (in the original database or Excel spreadsheet for example) or you used a combination of calculated fields and groups directly in Tableau. Prep allows you to handle your data cleanup directly and makes it very simple to see which fields are affected.

Data Cleaning In Tableau

Data Cleaning In Tableau Tutorial

  • Providing an Overview of Your Data Prior to Analyzing It

Data Cleaning In Tableau Public

Data Cleaning In Tableau

Before you even begin analyzing your data, Tableau Prep provides you with an overview of all of your fields as well as data histograms so you can view the frequency of the values in each field. By simply sorting any of these fields you can see which values are most frequent or infrequent within your dataset. A count of the total distinct records in each field is provided as well.

  • Documenting Your Cleanup Process

If you have previously used Tableau’s legacy data preparation screen, it was up to you to document your process in a tool outside of Tableau. Prep removes this grunt work and provides a clean and intuitive flow diagram of each step in your process. Not only does this allow you to keep track of what you have done, it allows others to pick up your Prep flow and quickly understand it too.

  • Repeatability

By saving a flow in Prep, you will be able to use the same process for data cleanup in the future. While this still requires manual execution, running the flow only requires the click of a button.

Tableau Prep’s Limitations:

  • Automation

Tableau Prep is not an ETL tool that you can automate to run without your interaction. It will not replace your current ETL process or stored procedures. For now, the only way to execute a Tableau Prep flow is directly in the tool itself.

Data Interpreter Tableau

  • Scheduling

You cannot set a schedule for executing your Prep flows. Unfortunately, this manual execution process means that it is not viable for reports that require regular data updates.

  • Exporting Format

Prep allows exporting the cleansed dataset as an extract or publishing directly to Tableau Server. However, if you want to use the data outside of Tableau, the only current option for export is as a csv.

  • Data Volume

Data Cleaning In Tableau Definition

While there are no published data volume limitations, large datasets are not handled well by Prep. When connecting to a dataset of 10M records, the data field histograms did not populate. Simply converting two fields from integers to dates and attempting to run the flow caused Prep to fail and return a message that stated, “An error has occurred while running the flow”. Until Tableau provides additional guidance, Prep should be primarily used for smaller datasets.

Data Cleaning Techniques In Tableau

As it exists now, there are limited use cases for using Tableau Prep without using Tableau Desktop. There are more mature and feature-rich data preparation tools out there that allow you to automate the data clean-up process, export the data however you would like, and schedule that export as well.

Tableau Data Preparation

However, Tableau Prep is a great improvement over the data preparation capabilities that previously existed in Tableau Desktop. By reducing the amount of manual work required in cleaning up data prior to importing it into Tableau, as well as having Prep bundled directly with Desktop, users will be able to focus more time on data analysis and less time on data clean-up.

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