1. Introducing the Dataset

 
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Joining and Transforming Data

14 lessons , 4 exercises

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Overview

This lesson provides a brief course overview and introduces the dataset we’ll use in the first half of the course.

Summary

  1. Course Overview (00:11)

    In the first half of the course, we’ll focus on how to merge datasets with tools in the Join tab. In the second half of the course, we’ll apply some of these Join tools and use Transform tools to perform simple profitability and trend analysis for a case study.

  2. Lesson Goal (00:31)

    In this lesson, we’ll examine various sales datasets from a pharmaceutical firm called Altavica.

  3.  Introducing the Data (00:39)

    Altavica has sales data covering four products: Lomina, Samtan, Tridesta, and Wedicare. This data is spread across multiple locations with one file for each year of sales data from 2012-2015. Each file contains sales information for each individual transaction, including date, sales price, quantity, product, and a customer ID number that identifies each purchaser.

    The company also has separate files that contain other related information. This includes a file that details the name and address of each customer, a file that lists sales associates assigned to each customer, and a file that details the form factor, dosage, and cost information for each product.

  4. Desired Outcome (01:53)

    The management of Altavica would like to compare the performance of various sales associates, as well as the profitability of each product. Before performing these analyses, they need to combine this information into a single master dataset. We’ll accomplish this use the various Join tools available in Alteryx.

Transcript

In this course, we'll take a deeper look at the tools available in the Join and Transform tabs on the tool palette.

In the first half of the course, we'll focus on how to merge datasets with the tools in the Join tab.

In the second half of the course, we'll apply some of these Join tools again and then use the tools and the Transform tab to perform simple profitability and trend analysis for an office supply retailer.

In this lesson, we'll examine various sales datasets from a pharmaceutical firm called Altavica.

Altavica has sales data spanning four years, covering four products. Lomina, Samtan, Tridesta and Wedicare.

The company sales data is currently stored in multiple locations with separate Excel files for each year from 2012 through 2015.

Each file contains sales information for each individual transaction including date, sales price, quantity, product, and a customer ID number that identifies each purchaser.

The company also has separate files that contain other related information. Let's run through each of these files.

First, there's a file that details the name and address of each customer.

Note that this file also contains a customer ID field.

Next, we have a file that lists a sales associate assigned to each customer. This file also contains the customer ID field.

Finally, we have a file that details the form factor, dosage and cost information for each product.

The management team at Altavica would like to be able to gain more insight into its sales. For example, they would like to compare the performance of various sales associates as well as the profitability of each product.

Before Altavica can perform these analysis, they need to combine this information into a single master dataset.

Throughout the remaining lessons in this course, we'll look at the various options available in Alltricks for merging data from different sources.

In the next lesson, we'll start by examining how we use Unions and Joins to merge datasets.