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What is Exploratory Data Analysis (EDA)

Chapter 4
Big Data Analytics for Entrepreneurial Success
In statistics, EDA is an approach to analyzing data sets to summarize their main characteristics, often with visual methods.
Published in Chapter:
First of All, Understand Data Analytics Context and Changes
Copyright: © 2019 |Pages: 33
DOI: 10.4018/978-1-5225-7609-9.ch004
Abstract
Big data marks a major turning point in the use of data and is a powerful vehicle for growth and profitability. A comprehensive understanding of a company's data, its potential can be a new vector for performance. It must be recognized that without an adequate analysis, our data are just an unusable raw material. In this context, the traditional data processing tools cannot support such an explosion of volume. They cannot respond to new needs in a timely manner and at a reasonable cost. Big data is a broad term generally referring to very large data collections that impose complications on analytics tools for harnessing and managing such. This chapter details what big data analysis is. It presents the development of its applications. It is interested in the important changes that have touched the analytics context.
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Chapter 4
Quality Improvement of Healthcare Services Through Data Analytics Processes
Exploratory Data Analysis (EDA) is a data analysis approach involving an initial, critical examination of the data to identify patterns and anomalies typically conducted using summary statistics and basic visualizations.
Published in Chapter: Quality Improvement of Healthcare Services Through Data Analytics Processes; From: Advancement in Business Analytics Tools for Higher Financial Performance
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Chapter 39
Machine Learning and Exploratory Data Analysis in Cross-Sell Insurance
Preliminary analysis of dataset in order to find important measures, metrics, features and relationship between measures so that we can gain an insight into trends, patterns, detect outliers in the dataset.
Published in Chapter: Machine Learning and Exploratory Data Analysis in Cross-Sell Insurance; From: Encyclopedia of Data Science and Machine Learning
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Chapter 4
Adaptive Neural Algorithms for PCA and ICA
An approach based on allowing the data itself to reveal its underlying structure and model heavily using the collection of techniques known as statistical graphics.
Published in Chapter: Adaptive Neural Algorithms for PCA and ICA; From: Encyclopedia of Artificial Intelligence
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Chapter 69
Data Science in the Database: Using SQL for Data Preparation
Lightweight analysis of data that uses descriptive statistics, graphics and other tools in order to describe the data and discover whether any problems are present. Data analysts use EDA as a first approach to a dataset in order to gain an understanding of what it means, what kind of values it contains, and what issues the data may have.
Published in Chapter: Data Science in the Database: Using SQL for Data Preparation; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
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