Your sales data files for the different regions are stored in different formats, and your orders from the South are actually multiple files. For more information about connecting to data, see Connect to Data (Link opens in a new window). You can have multiple Input steps and some might include multiple data files. Tip: The Input step is the ingestion point for your data and the starting point for your flow. From there you will start building a workflow or "flow", as it's called in Tableau Prep, and add more steps to take action on your data as you go. To get started, the first step is to connect to your data and create an Input step. The first thing you see when you open Tableau Prep Builder is a Start page with a Connections pane, just like Tableau Desktop.
Tableau prep logo trial#
You download the product, or sign up for a free trial (Link opens in a new window) and decide to give it a try. You also notice a lot of creative data entry in the different files, and that one region even has a separate file for each year!īefore you can start analyzing the data in Tableau, you'll have to do some serious data cleaning first, and it's going to be a long night.Īs you rummage for restaurant menus to order some dinner, you remember that Tableau has a product called Tableau Prep that might help you with your Herculean data cleaning tasks. Your boss thinks that's a great idea and wants you to get right on that.Īs you start gathering all the data you'll need, you notice that the data has been collected and tracked differently for each region. You suggest that he use Tableau Desktop to do that. Your boss wants to analyze product sales and profits over the last four years for the company. You work at the headquarters for a large retail chain. You'll need to do this if completing this tutorial on the web. app/Contents/help/Samples/en_US/Superstore FilesĪlternatively, download the sample files from these links and create a Samples directory and a South sub-directory. (Mac) /Applications/Tableau Prep Builder. (Windows) C:\Program Files\Tableau\Tableau Prep Builder \help\Samples\en_US\Superstore Files
Tableau prep logo install#
To complete the tasks in this tutorial, you need to install Tableau Prep Builder, or if web authoring is enabled on your server version 2020.4 or later, you can also try the steps on the web.Īfter installing Tableau Prep Builder on your machine, you can also find the sample files in the following location : Otherwise you can download the free trial (Link opens in a new window). To install Tableau Prep Builder before continuing with this tutorial, see Install Tableau Desktop or Tableau Prep Builder from the User Interface (Link opens in a new window) in the Tableau Desktop and Tableau Prep Builder Deployment guide. Watch for tips along the way to gain insights into how Tableau Prep helps you clean and shape your data for analysis. If you are using a previous version, your results may differ. This tutorial uses the most current version of Tableau Prep Builder. Using the sample data sets that come with Tableau Prep, you will walk through creating a flow for Sample Superstore. This tutorial introduces you to the common operations that are available in Tableau Prep. This tutorial was designed using Tableau Prep Builder, but can also be done on the web with some noted exceptions. O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.Note: Starting in version 2020.4.1, as a Creator, you can also create and edit flows on the web. Get Tableau Prep: Up & Running now with the O’Reilly learning platform. Irregular number of records: Is there a consistent number of rows for certain dimensions, and does this. Outliers: Do the values lie inside a certain range except for one or a few that sit outside of it?
Minimum, maximum, and range of values: Does the range between the minimum and maximum values make sense?ĭata outside of limits: Are there natural limits in the data, like 100%, or current dates that cannot be exceeded but have been?
All of these factors form the foundation of the data set profile, which comprises these factors: Determining the data set’s level of granularity will help you to identify how many unique records there are, or whether there are duplicate records that you need to remove in the data preparation process. Equally important is understanding the number and variance of the categorical data fields of the data set. As discussed in earlier chapters, understanding the types of data you have in the data set is essential to your analysis. By profile, I mean the characteristics of the data set.
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