If you want to learn about data analytics and data mining then keep reading... 2 comprehensive manuscripts in 1 book Data Analytics: An Essential Beginner's Guide To Data Mining, Data Collection, Big Data Analytics For Business, And Business Intelligence Concepts Data Mining: The Data Mining Guide for Beginners, Including Applications for Business, Data Mining Techniques, Concepts, and More With this book, not only will you understand all the internal nitty-gritties about data analytics and data mining, you will also understand why data analytics and data mining is changing the business arena. You'll realize that the high-performance analytics will enable you to do stuff that you never thought about before probably because the volumes of data were just too big (among other reasons) and so much more. Here are just some of the topics that are discussed in the first part of this book: Overview Of Data Analytics: What Is Data Analytics (And Big Data Analytics)? Data Analytics And Business Intelligence Data Analysis And Data Analytics Data Mining Data Collection Types Of Data Analytics The Process: The Lifecycle Of Big Data Analytics Behavioral Analytics: Using Big Data Analytics To Find Hidden Customer Behavior Patterns Further Pattern Discovery In Advanced Analytics: Machine Learning And Much, Much More In part 2 of this book, you will learn the following: Model creation How to prepare your data How to clean your data Data Mining Similarity and distances of data The effect of data distribution Association pattern mining What is cluster analysis? What is an outlier in data mining? How to deal with outliers in data mining Methods of identifying outliers in data Applications of data mining in the business industry So if you are serious about becoming an expert in data analytics and data mining, start with this book by clicking "add to cart"!

El big data, entendido como la gestión y el almacenamiento masivo de datos, es una tendencia por explotar a día de hoy. La industria audiovisual, consciente de ello, empieza a orientar estrategias de negocio con ideas de personalización de contenidos, segmentación de perfiles o predicción de tendencias. Comprender todas las posibilidades que nos ofrece el big data supone entender las dinámicas internas del negocio, así como las fuentes de datos de las que podemos extraer información y la interacción que podemos realizar con ellas. Y también nos permite formular mejores preguntas y tomar decisiones acertadas. Este libro ofrece un recorrido por el proceso de gestión de datos en la empresa, con introducción de explicaciones técnicas y especial atención a la toma de decisiones del business intelligence.

Las organizaciones han usado estrategias, como la inteligencia de negocio, para tomar mejores decisiones a partir de los datos. Actualmente, en la era de los datos, nuestros clientes son más inteligentes, están más informados y ya no son tan leales con nuestra marca. Esperan experiencias inolvidables y profundamente personalizadas en cada una de las interacciones con nuestra organización. Como resultado, las organizaciones están obligadas a transformar sus estrategias para conocer mejor las necesidades y preferencias de sus clientes, basándose en una enorme cantidad de datos.

This book gathers selected papers presented at the Inventive Communication and Computational Technologies Conference (ICICCT 2022), held on May 12–13, 2022, at Gnanamani College of Technology, Tamil Nadu, India. The book covers the topics such as Internet of Things, social networks, mobile communications, big data analytics, bio-inspired computing, and cloud computing. The book is exclusively intended for academics and practitioners working to resolve practical issues in this area.

A keyword listing of serial titles currently received by the National Library of Medicine.

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

This book constitutes the proceedings of the 5th International Conference on Applied Informatics, ICAI 2022, which took place in Arequipa, Peru, in October 2022. The 32 papers presented in this volume were carefully reviewed and selected from 90 submissions. The contributions are divided into the following thematic blocks: Artificial Intelligence; Data Analysis; Decision Systems; Health Care Information Systems; ICT-Enabled Social Innovation; Image Processing; Robotic Autonomy; Software Architectures; Software Design Engineering.