#Tableau prep install how to
#Tableau prep install install
#Tableau prep install license
#Tableau prep install download

#Tableau prep install install

This will also install the necessary dependencies. I am using the Anaconda distribution of Python, so I will just go ahead and install TabPy Server by typing pip install tabpy in my Anaconda prompt: You also need to have TabPy Server library installed. To use Python with Tableau Prep or Desktop, you, of course, need to have a distribution of Python installed.

Fortunately for our demo, we can do a fuzzy match using Python. Unfortunately, fuzzy matching is not supported by default in Tableau Prep at the moment. One way to go about this problem would be to use fuzzy matching, which is a technique of finding strings that match the pattern in a target string approximately rather than exactly. We can go ahead and match each account manually in Prep, but this could take hours if we have hundreds of accounts. These are typical errors when entering company names manually. Inc, Ltd, SA) as the prefix or suffix, and/or some contain typos in the company name. Some account names have company types (e.g. The others have not been joined because the names do not match correctly. However, when attempting to join on account, we only join about 10% of accounts successfully.

We have two datasets: one with sales per account for last year and the other with the sales representatives assigned to each of our accounts:Ībove: Sales representatives responsible for each accountĪt first glance, the solution is straightforward: we simply have to join the two datasets on the account field, and we would have the amount of sales generated by each sales representative. For this demo, we will attempt to find out how much each of the 15 sales representatives in an imaginary company sold last year.

#Tableau prep install how to

I will explain how to use Python in Tableau Prep using the demo use case below, but before proceeding to the Python part, let me give you some background on what I am trying to achieve with Python in this particular case. A blog on how to use Python in Tableau Desktop will be coming soon. Please note that using Python in Tableau Prep is different than using Python on Tableau Desktop. With Python, you can do all of this and so much more, extending the power of Tableau Prep whilst staying within the boundaries of a Tableau Prep workflow. But sometimes, you need to apply a function that has no equivalent in Prep, want to extract some data using an API interface or even apply some machine learning or natural language processing algorithms. It offers a lot of tools to pre-process and transform your data.

#Tableau prep install license

Note: If you ever need to reactivate your product key for any reasons (for example, license has expired and then renewed), you can do so by going to the menu Help > Manage Product Keys, a pop-up will appear where you can deactivate your old product key as well as activate a new product key.Tableau Prep has improved considerably since it was launched. Your Tableau Prep Builder installation is now completed and activated. Then click the Activate button to finish.

In the next screen, enter your product key.

Launch the Tableau Prep Builder, you will see the following pop-up, click Activate with a product key.

Once the installer finishes running, click the Close button in the next screen after the installation is completed.

Click the Yes button in the Windows User Account Control Pop-up to allow installer to proceed (applies to Windows platform only).Check the box next to 'I have read and accept the terms of the license agreement.' Then click the Install button.

#Tableau prep install download

Download the Tableau Prep installer from Tableau Support website at.After your Tableau license purchase has been finalized, use these instructions to install Tableau Prep Builder.