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Smarter Decisions - The Intersection of Internet of Things and Decision Science

You're reading from   Smarter Decisions - The Intersection of Internet of Things and Decision Science A comprehensive guide for solving IoT business problems using decision science

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781785884191
Length 392 pages
Edition 1st Edition
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Author (1):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
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Table of Contents (10) Chapters Close

Preface 1. IoT and Decision Science FREE CHAPTER 2. Studying the IoT Problem Universe and Designing a Use Case 3. The What and Why - Using Exploratory Decision Science for IoT 4. Experimenting Predictive Analytics for IoT 5. Enhancing Predictive Analytics with Machine Learning for IoT 6. Fast track Decision Science with IoT 7. Prescriptive Science and Decision Making 8. Disruptions in IoT 9. A Promising Future with IoT

Exploratory data analysis

This part of the problem solving stack is also called "Confirmatory data analysis". Generally, the problems that we touch base over the Internet and other learning resources explain a stack called "ECR" that can be extended as Exploratory Data Analysis + Confirmatory Data Analysis + Root Cause Analysis. This is the same approach that we have considered-Exploratory Data Analysis (EDA)-where we understand "What" happened, then CDA, that is, Confirmatory Data Analysis, where we cement the results from our exercises using statistical tests. Finally, we will answer the "Why" question using Root Cause Analysis. In our current approach, we have the same approach but a slightly different naming convention. We have broken down the steps into more granular ones:

Exploratory data analysis

We have now reached the EDA phase, that is, we will now validate the insights and patterns that we observed in the data. Let's start with understanding how we are going...

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