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 now! 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
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

Arrow left icon
Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis 2. Data Preprocessing FREE CHAPTER 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Chapter 1. Introduction to Data Analysis

Data analysis is the process of organizing, cleaning, transforming, and modeling data to obtain useful information and ultimately, new knowledge. The terms data analytics, business analytics, data mining, artificial intelligence, machine learning, knowledge discovery, and big data are also used to describe similar processes. The distinctions of these fields probably lie more in their areas of application than in their fundamental nature. Some argue that these are all part of the new discipline of data science.

The central process of gaining useful information from organized data is managed by the application of computer science algorithms. Consequently, these will be a central focus of this book.

Data analysis is both an old field and a new one. Its origins lie among the mathematical fields of numerical methods and statistical analysis, which reach back into the eighteenth century. But many of the methods that we shall study gained prominence much more recently, with the ubiquitous force of the internet and the consequent availability of massive datasets.

In this first chapter, we look at a few famous historical examples of data analysis. These can help us appreciate the importance of the science and its promise for the future.

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