Session 1 Predictive Analytics

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Alteryx Predictive Analytics
Data Prep and Investigation
Welcome!
Cailin Swingle, Solutions Engineer

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Participation
• We will be asking for interaction
and feedback during the class.
• At the top of the screen click on
Participants
• Interaction icons:
• Hand
• Green check mark
• Red ‘X’
• Go slower/faster
• Emoticons

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Chat and Q&A
• Feel free to ask questions!
• Ask verbally or
• Q&A tab
• Type your question here

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Session 1– Data Prep and Investigation
• Understanding your data
• Determining predictor variables
• Transforming variables
Session 2– Model Build and Assessment
Session 3- Cluster Analysis
Session 4- Time Series
Course Outline

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• It is expected that you are familiar with building workflows in Alteryx. We
will not be going over how to use the standard Alteryx tools.
• It is helpful to have some background with Predictive Analysis.
• The focus is on how to do Predictive Modeling in Alteryx, not for example
explaining what a regression is.
Assumptions

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A quick service restaurant chain is interested in mailing coupons to local
neighborhoods to grow their customer base. They want to know which
households are most likely to become customers and which households would
be the most valuable in terms of revenue.
Data available:
• Customer and non-customer households with additional fields appended
from the Experian ConsumerView file
• Household level restaurant (food away from home) expenditure and
other household characteristics from the Bureau of Labor Statistics
Objectives:
• To determine which households to mail to, construct a model that
predicts the likelihood that a household will be a customer
• To find out which households will spend the most, build a predictive
model that estimates restaurant expenditure
Business Case

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Alteryx Engine

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Things to look for:
• Constants (Unique Values = 1)
• Zero’s in your numeric data (Min = 0)
• Numeric fields that have few unique values
• “This field has a small number of unique values, and
appears to be a categorical field. Consider changing
the field data type to "string".”
• Rare characteristics (Min Value Count)
• “Some values of this field have a small number of
value counts. If Appropriate, consider combining
some value levels together.”
Field Summary Report

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Summary
When to use Scatterplot vs. Plot of Means vs. Association Analysis
• Scatterplot
– Shows how two variables relate to one another graphically. Can reveal non-
linear relationships between variables and show if one variable must be
transformed to model the true relationship between the two. Best when
both variables are interval or ratio.
• Plot of Means
– Takes a numeric or binary categorical target variable along with a
categorical predictor variable and plots the mean of the response field for
each of the categories (levels) of the predictor variable.
• Association Analysis
– This tool should be used to see which variables are correlated with one
another. Makes the most sense when all variables are interval or ratio.

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Support Resources
• Technical support 8am – 8pm Eastern
• Email: clientservices@alteryx.com
• Phone: (888) 836-4274
• Choose option 2
• WebEx training – live and recorded
• Community

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Thank You!