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1. What is Tableau Prep
This lesson explains the data preparation use cases of Tableau Prep's and its advantages and disadvantages over Alteryx.
This goal of this lesson is to discover the role of Tableau Prep in Data Manipulation
Why Use Tableau Prep
Tableau Desktop depends on structured data to function properly. User-created data, questionnaire data and web data tend to be in an unstructured format. If you want to use data sources like these in Tableau Desktop, you need to clean them up.
Tableau Prep has the tools and functions to handle all these unstructured data types. Tableau Prep can convert any unclean data into a format which is easily read by Tableau Desktop
Tableau Prep vs Excel
Excel can do much of what Tableau Prep can already achieve. But, Tableau Prep has the upper hand for data preparation for 1 main reason. Its drag and drop interface makes it much faster than Excel. Tableau Prep is also capable of connecting to much larger datasets than Excel
Tableau Prep vs Alteryx
Alteryx has an easy to use drag and drop interface to Tableau Prep. It can also connect to very large datasets. Also, Alteryx is far more customizable and includes machine learning algorithms.
Tableau Prep is far easier to use. And because it comes with Tableau Desktop at no extra cost, it is far more cost-effective than Alteryx.
Through this course, we'll introduce a data preparation application called Tableau Prep.
In this first lesson, we'll discover the role of Tableau Prep in data manipulation. We'll start by asking the question why we might need Tableau Prep.
We'll then compare Tableau Prep to similar data manipulation applications.
We'll finish with a quick summary on what we'll cover in the rest of this course.
Sometimes our data just isn't ready to be interpreted by Tableau Desktop. This data can come from sources such as questionnaires, human inputted data, and data pulled directly from the web. Tableau Prep can take any of these data sources and manipulate them into a format that Tableau Desktop can easily understand. Before the creation of Tableau Prep, Tableau Desktop users had to rely on third party software such as Excel or Alteryx. With Tableau Prep, these users have access to a tool which is arguably easier to use. Let's examine why.
In almost all cases, Tableau Prep is a superior alternative to Excel.
Unlike Excel, Tableau Prep is a purpose-built data manipulation tool. It's ideal for casual Excel users because data manipulation in Excel can be quite cumbersome. The lack of a drag and drop interface means that Excel users must heavily rely on formulas.
Tableau Prep is also ideal for experienced Excel users because it can manipulate data far more quickly and efficiently. Tableau Prep can also handle much larger datasets from a wider variety of sources.
Alteryx on the other hand can challenge Tableau Prep in some areas.
For those unfamiliar with Alteryx, Tableau Prep is by far is the superior option as it's much easier to learn. However, experienced Alteryx users may well prefer to stick with what they know. They've already surpassed Alteryx's tough learning curve and Alteryx offers far more customizable functionality than Tableau Prep. Alteryx also offers an impressive array of data science tools such as machine learning algorithms.
That being said, Tableau Prep can still entice experienced Alteryx users.
Alteryx carries a hefty price tag while Tableau Prep is included with a Tableau Desktop license.
Experienced Alteryx users may wish to part with some of the superior functionality of Alteryx in order to realize significant savings.
Now that we know what Tableau Prep does and how it compares to other data manipulation products, let's have a look at what we'll cover in the rest of this course.
We'll start this course by examining our dataset and connecting it to Tableau Prep. We'll then examine Tableau Prep's user interface and clean our data.
We'll use a variety of tools to remove nulls, trim spaces and more.
Finally, we'll manipulate text data by splitting fields and grouping and replacing similar values.
In the next lesson, we'll examine our dataset to see what changes we need to make to prepare it for Tableau Desktop.