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Predictive Analytics Using Rattle and Qlik Sense

You're reading from  Predictive Analytics Using Rattle and Qlik Sense

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781784395803
Pages 242 pages
Edition 1st Edition
Languages
Authors (2):
Ferran Garcia Pagans Ferran Garcia Pagans
Profile icon Ferran Garcia Pagans
Fernando G Pagans Fernando G Pagans
Profile icon Fernando G Pagans
View More author details

Table of Contents (16) Chapters

Predictive Analytics Using Rattle and Qlik Sense
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Ready with Predictive Analytics 2. Preparing Your Data 3. Exploring and Understanding Your Data 4. Creating Your First Qlik Sense Application 5. Clustering and Other Unsupervised Learning Methods 6. Decision Trees and Other Supervised Learning Methods 7. Model Evaluation 8. Visualizations, Data Applications, Dashboards, and Data Storytelling 9. Developing a Complete Application Index

Summary


In this chapter, we saw how to use Qlik Sense to create an application that helps us to analyze our customer data. We used a simple dataset with just 440 customers that we downloaded from the University of California website mentioned earlier. The dataset contained only two dimensions—channel and region—and six measures—Fresh, Frozen, Milk, Grocery, Delicatessen, and Detergents_Paper.

We learned how to load a dataset from a CSV file. We created a data model and uploaded additional tables created in a spreadsheet editor. Finally, we saw that we can create additional fields in a table using the spreadsheet editor or the data load editor. We also saw that the data load editor provides a lot of control over the data.

After creating the data model, we learned what associative logic is and how a business user can slice and dice his data using it.

Finally, we learned how to create basic visualizations using Qlik Sense, and we created our first Qlik Sense app.

In the next chapter, we'll use...

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