Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Predictive Analytics using Rattle and Qlik Sense

You're reading from   Predictive Analytics using Rattle and Qlik Sense Create comprehensive solutions for predictive analysis using Rattle and share them with Qlik Sense

Arrow left icon
Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781784395803
Length 242 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Ferran Garcia Pagans Ferran Garcia Pagans
Author Profile Icon Ferran Garcia Pagans
Ferran Garcia Pagans
Arrow right icon
View More author details
Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Ready with Predictive Analytics FREE CHAPTER 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

Chapter 2. Preparing Your Data

The French term mise en place is used in professional kitchens to describe the practice of chefs organizing and arranging the ingredients up to a point where it is ready to be used. It may be as simple as washing and picking herbs into individual leaves or chopping vegetables, or as complicated as caramelizing onions or slow cooking meats.

In the same way, before we start cooking the data or building a predictive model, we need to prepare the ingredients-the data. Our preparation covers three different tasks:

  • Loading the data into the analytic tool
  • Exploring the data to understand it and to find quality problems with it
  • Transforming the data to fix the quality problems

We say that the quality of data is high when it's appropriate for a specific use. In this chapter, we'll describe characteristics of data related to its quality.

As we've seen, our mise en place has three steps. After loading the data, we need to explore it and transform it...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image