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1. Introducing the Data
In this lesson, we introduce the dataset that we’ll be analyzing and the topics that we’ll cover in this course.
To explore more Kubicle data literacy subjects, please refer to our full library.
Strengths and Limitations of Alteryx (00:11)
Alteryx is great at joining, manipulating, and analyzing data, but does not have a strong suite of built in data visualization capabilities. While Alteryx is great for manipulating spatial data, consider using a different tool like Tableau or Power BI for visualizing spatial data.
Introducing the Dataset (00:51)
We’ll work with a dataset from a pharmaceutical company that details sales of products to customers in England. This dataset contains street address, longitude, and latitude data for each customer.
Course Overview (01:32)
We’ll cover three main topics in this course. First, we’ll convert the coordinate information into map points, and calculate the distance between two points. We’ll then perform more complex analyses, such as creating heat maps and trade areas. Finally, we’ll look at how to prepare data for export to data visualization software.
In this course, we'll look at the spatial data and mapping capabilities available in Alteryx.
Before diving into the data set and what we'll accomplish in this course, it's important to understand the strengths and limitations of Alteryx.
Alteryx is great tool for joining, manipulating, and analyzing data.
However, Alteryx does not have a strong suite of built-in data visualization capabilities.
Accordingly, while Alteryx is a great tool for manipulating spatial data, you should consider using a different application, like Tableau or Power BI, to display this data in a visual format.
Throughout this course, we'll look at how to use Alteryx to manipulate and analyze spatial data.
We'll be working with a data set from a pharmaceutical company.
This data set details sales of several products to customers in England.
Notice that the company has relatively detailed information on their customer locations.
Specifically, the data set contains street, town, county, and post code information.
More importantly, the data set also contains specific GPS coordinates for every customer.
While they have rightly realized that this information can be valuable to their business, they don't have the expertise to properly analyze this data.
Over the next few lessons, we'll look at the basic principles behind mapping data.
We'll learn how to turn our GPS coordinates into map points and calculate the distance between two points.
We'll then learn how to further manipulate this data to perform more complex analyses, such as creating heat maps and trade areas.
Finally, we'll explore how to prepare this data for export to visualization applications, like Tableau, allowing us to leverage the strengths of multiple platforms.
In the next lesson, we'll start at the beginning and explain what geographical data is and how to create map points in Alteryx.