You have gained many new Alteryx skills over the past several courses. After introducing the case study, this chapter will test your knowledge of combining data, working with dates, and cleaning up general data. You’ll also get a surprise assignment added by your boss!

Putting your Alteryx knowledge to the test

Data analysis process

Input order data

Add region data

Formatting dates

An added assignment

Data Blending and Date Conversion

Get ready to transform some data! This chapter will allow you to pivot, parse, clean, and calculate data. Once the data is ready, you’ll join it to the data from the previous chapter in preparation for any upcoming analysis.

Data transformations

Options

Crosstab

Transpose

Summarize

Transformation tools in Alteryx

Transform order details

Parse categories

Calculate profitability

Bring it all together

Data Transformations

Your data is finally ready for analysis! After carefully prepping and combining your data, you’ll use this chapter to transform, calculate, and summarize your way to the answers asked of you by the company bosses. 

Ready, set, analyze

What tool group?

Top 25 orders

Day of week analysis

Category analysis - region

Sub-category analysis

Congratulations!

Ready, Set, Analyze

Metadata sheet

Exercises and Datasets

DataCamp vs. Local Experience

Are you ready to explore the power of Alteryx Designer with a focus on retail sales data? In this case study, you will analyze data from a fictional department store to tackle questions related to sales performance.
Using Alteryx Designer, you'll prepare, blend, and analyze data to help answer questions about sales trends and patterns. This hands-on course will guide you through creating workflows to analyze product performance, helping you identify key drivers of sales success.
By the end of this case study, you'll have the skills to leverage Alteryx Designer for comprehensive sales analysis, enabling informed business decisions and strategic planning. Dive into data and transform it into actionable insights with Alteryx Designer.

Ready to harness the capabilities of Alteryx Designer for retail analytics? This case study will take you through a comprehensive exploration of sales data from a fictional department store, focusing on enhancing your understanding of sales performance and strategic decision-making.<br><br> 
<h2>Dive Into Data Analysis with Alteryx Designer</h2>
Using Alteryx Designer, you'll prepare, blend, and analyze data to uncover insights into sales trends and patterns. This hands-on course guides you through creating workflows to analyze product performance, helping you identify key drivers of sales success. By the end of this case study, you'll possess the skills necessary to leverage Alteryx Designer for comprehensive sales analysis, enabling informed business decisions and strategic planning.<br><br> 
<h2> Apply Your Alteryx Skills and Get Certified</h2>
You've acquired substantial Alteryx knowledge; now, put it to the test! This case study provides an opportunity to apply all the skills you have learned as part of the Alteryx Fundamentals track to a real-world example. During the course, you'll review data importing and blending, simple analytics and aggregation techniques, data parsing and cleansing, and workflow documentation. This case study is designed to review the concepts and skills needed to take (and pass!) the Alteryx Core Certification exam. Put that knowledge to work and get certified!

Data Preparation in Alteryx

Master Alteryx Designer with this case study on retail sales data analysis for strategic insights and informed decisions.

Case Study: Analyzing Sales Data in Alteryx

Explore Alteryx Designer in a retail data case study to boost sales analysis and strategic decision-making.

Alteryx Fundamentals

A table has 3 columns: Department, Month, and Employee Count. You need a table with a separate column for each month and the department as rows.

A table of sales data has the columns Department, Q1, Q2, Q3 and Q4. You instead want a table with Department, Quarter, and Sales columns.

You have a table of sales data with the columns Region, Sales Rep, and Quota. You must aggregate the data to create a total quota by region.

Transformation tools in Alteryx

Case Study: Analyzing Sales Data in Alteryx

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