1. Course Introduction

 
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Applying Parsing and Formula Tools

11 lessons , 2 exercises

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Overview

In this lesson, we introduce the case that we will examine in this course as well as the tools we’ll use for our analysis.

Summary

  1. Course Overview (00:11)

    In this course, we’ll look at how to use parsing and formula tools to prepare a dataset for and perform analysis.

  2. Manipulating Date Data (00:17)

    Alteryx can only read date data in a specific format, so you’ll likely need to convert your date information before it is usable. We’ll apply a DateTime tool to a sample dataset populated with different common date formats to understand how this works.

  3. Introducing the Case (00:32)

    In the rest of the course, we’ll work with a sales dataset from a software company. This company sells user licenses for their software to businesses. The dataset consists of the customer name, the number of users at that company, revenue and cost data, address and region information, sales date, and sales person.

    The company has asked us to parse the address data and add new customer size and geographic categories to prepare for further analysis. They also want us to break out profit margin information by customer size and geography, calculate a 7-day moving average of revenue, as well as quarterly revenue and the market share of various geographic areas.

  4. Tools Used in this Course (01:39)

    We’ll look at how we can use the DateTime, Text to Columns, Multi-Field Formula, and Formula tools to parse data. We’ll also focus on how we can use various formula expressions, the Generate Rows tool, and the Multi-Row Formula tool to perform our analysis.

Transcript

In this course, we'll look at how to use parsing and formula tools to prepare a dataset for analysis.

In this lesson, we'll introduce our datasets and outline the course.

Alteryx can only read date data that's in a specific format so you'll likely need to convert your date information before it's usable.

We'll use a sample dataset populated with different common date formats to understand how this works.

In the remainder of the course, we'll work with a sales dataset from a software company.

This company sells user licenses of their software to other businesses.

The dataset consists of customer names, the number of users at that company, revenue and cost data, address and region information, sales date and the sales person.

The company would like to gain further insight into this data.

As part of this analysis, the company has asked us to parse the address data and add new customer size and geographic categories to prepare for further analysis.

They would then like us to break up profit margin information by customer size and geography, and calculate a seven-day moving average of revenue.

Finally, the company would like to see quarterly revenue and the market share of various geographic areas.

We'll lean heavily on the tools and the preparation and parse tabs to accomplish these tasks. Specifically, we'll look at how we can use the DateTime tool, Text to Columns tool, Formula tool, and Multifield Formula tool to parse data.

We'll also focus on how we can use various formula expressions, the Generate Rows tool, and the Multi-row tool to perform our analysis.

In the next lesson, we'll start our course by learning how to work with date and time data in Alteryx.

Applying Parsing and Formula Tools

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