DATA EXPLORATION AND DATA PREPARATION PHASE
DATA EXPLORATION AND DATA PREPARATION PHASE

Author: Dr. Raja Sarath Kumar Boddu

Publisher: Xoffencerpublication

Published: 2021-09-16

Total Pages: 254

ISBN-13: 9394707239

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Over the course of the last decade, the amount of data with which one must deal has skyrocketed to levels that are difficult to fathom, while at the same time, the cost of storing data has steadily decreased. Private firms and research organizations collect terabytes of data about their customers' interactions, commerce, and social media, as well as sensors from devices such as mobile phones and vehicles. This data is used for a variety of purposes, including marketing and advertising. Figuring out how to make sense of all this data is one of the most difficult challenges of our day. The analysis of large amounts of data comes into play at this point. Big Data Analytics entails, for the most part, the gathering of data from a variety of sources, the management of this data in such a manner that it can be utilized by analysts, and the delivery of data products that are beneficial to the organization's business.

Data Preparation for Data Mining
Data Preparation for Data Mining

Author: Dorian Pyle

Publisher: Morgan Kaufmann

Published: 1999-03-22

Total Pages: 566

ISBN-13: 9781558605299

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This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mining in order to maximize mining performance.

Focusing Solutions for Data Mining
Focusing Solutions for Data Mining

Author: Thomas Reinartz

Publisher: Springer

Published: 2008-10-10

Total Pages: 317

ISBN-13: 3540483160

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In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing. The part devoted to the development of focusing solutions opens with an analysis of the state of the art, then introduces the relevant techniques, and finally culminates in implementing a unified approach as a generic sampling algorithm, which is then integrated into a commercial data mining system. The last part evaluates specific focusing solutions in various application domains. The book provides various appendicies enhancing easy accessibility. The book presents a comprehensive introduction to focusing in the context of data mining and knowledge discovery. It is written for researchers and advanced students, as well as for professionals applying data mining and knowledge discovery techniques in practice.

Bridging the Socio-technical Gap in Decision Support Systems
Bridging the Socio-technical Gap in Decision Support Systems

Author: Ana Respício

Publisher: IOS Press

Published: 2010

Total Pages: 616

ISBN-13: 1607505762

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Presents the advances in decision support theory and practice with a focus on bridging the socio-technical gap. This book covers a wide range of topics including: Understanding DM, Design of DSS, Web 2.0 Systems in Decision Support, Business Intelligence and Data Warehousing, Applications of Multi-Criteria Decision Analysis, and more.

Data Mining: Foundations and Practice
Data Mining: Foundations and Practice

Author: Tsau Young Lin

Publisher: Springer Science & Business Media

Published: 2008-08-20

Total Pages: 562

ISBN-13: 354078487X

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The IEEE ICDM 2004 workshop on the Foundation of Data Mining and the IEEE ICDM 2005 workshop on the Foundation of Semantic Oriented Data and Web Mining focused on topics ranging from the foundations of data mining to new data mining paradigms. The workshops brought together both data mining researchers and practitioners to discuss these two topics while seeking solutions to long standing data mining problems and stimul- ing new data mining research directions. We feel that the papers presented at these workshops may encourage the study of data mining as a scienti?c ?eld and spark new communications and collaborations between researchers and practitioners. Toexpressthevisionsforgedintheworkshopstoawiderangeofdatam- ing researchers and practitioners and foster active participation in the study of foundations of data mining, we edited this volume by involving extended and updated versions of selected papers presented at those workshops as well as some other relevant contributions. The content of this book includes st- ies of foundations of data mining from theoretical, practical, algorithmical, and managerial perspectives. The following is a brief summary of the papers contained in this book.

Big Data Management And Analytics
Big Data Management And Analytics

Author: Brij B Gupta

Publisher: World Scientific

Published: 2023-12-05

Total Pages: 288

ISBN-13: 9811257132

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With the proliferation of information, big data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge.Big data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of big data; from the preliminary level to specific case studies. It will help readers gain knowledge of the big data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of big data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a big data management system.Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using machine learning techniques, Spark's scalable machine learning techniques, modeling a big data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing big data and its applications including in healthcare and finance.

Data Analytics Applied to the Mining Industry
Data Analytics Applied to the Mining Industry

Author: Ali Soofastaei

Publisher: CRC Press

Published: 2020-11-12

Total Pages: 273

ISBN-13: 0429781776

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Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors

Big Data Analytics
Big Data Analytics

Author: Arun K. Somani

Publisher: CRC Press

Published: 2017-10-30

Total Pages: 399

ISBN-13: 1351180320

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The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.

Applying Computational Intelligence
Applying Computational Intelligence

Author: Arthur Kordon

Publisher: Springer Science & Business Media

Published: 2009-11-28

Total Pages: 470

ISBN-13: 3540699139

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In theory, there is no difference between theory and practice. But, in practice, there is. Jan L. A. van de Snepscheut The ?ow of academic ideas in the area of computational intelligence has penetrated industry with tremendous speed and persistence. Thousands of applications have proved the practical potential of fuzzy logic, neural networks, evolutionary com- tation, swarm intelligence, and intelligent agents even before their theoretical foundation is completely understood. And the popularity is rising. Some software vendors have pronounced the new machine learning gold rush to “Transfer Data into Gold”. New buzzwords like “data mining”, “genetic algorithms”, and “swarm optimization” have enriched the top executives’ vocabulary to make them look more “visionary” for the 21st century. The phrase “fuzzy math” became political jargon after being used by US President George W. Bush in one of the election debates in the campaign in 2000. Even process operators are discussing the perf- mance of neural networks with the same passion as the performance of the Dallas Cowboys. However, for most of the engineers and scientists introducing computational intelligence technologies into practice, looking at the growing number of new approaches, and understanding their theoretical principles and potential for value creation becomes a more and more dif?cult task.