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Big Data Analytics Methods

Author: Peter Ghavami

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2019-12-16

Total Pages: 282

ISBN-13: 1547401583

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Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Download or read book Big Data Analytics Methods written by Peter Ghavami and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-12-16 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.

Big Data Analytics

Author: Saumyadipta Pyne

Publisher: Springer

Published: 2016-10-12

Total Pages: 276

ISBN-13: 8132236289

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This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Book Synopsis Big Data Analytics by : Saumyadipta Pyne

Download or read book Big Data Analytics written by Saumyadipta Pyne and published by Springer. This book was released on 2016-10-12 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Data Analytics and Big Data

Author: Soraya Sedkaoui

Publisher: John Wiley & Sons

Published: 2018-05-24

Total Pages: 224

ISBN-13: 1119528054

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The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.

Book Synopsis Data Analytics and Big Data by : Soraya Sedkaoui

Download or read book Data Analytics and Big Data written by Soraya Sedkaoui and published by John Wiley & Sons. This book was released on 2018-05-24 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.

Big Data Analytics Methods

Author: Peter Ghavami

Publisher: Createspace Independent Publishing Platform

Published: 2016-03-06

Total Pages: 304

ISBN-13: 9781530414833

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Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensemble of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods are covered. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. This book is ideal as a text book for a course or as a reference for data scientists, data engineers, data analysts, Business intelligence practitioners, and business managers. It covers 10 chapters that discuss natural language processing (NLP), data visualization, prediction, optimization, artificial intelligence, regression analysis, cox hazard model and many analytics use case examples with applications in healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services. Big Data Analytics Methods Is a must read for those who wish to gain confidence and knowledge about big data and advanced analytics techniques. Read this book and confidently speak, lead and guide others about machine learning, neural networks, NLP, deep learning, and over 100 other analytics techniques. This book is fun and easy to read. It starts with simple and broad explanation of methods and gradually introduces more technical terms and techniques layer by layer. It finally introduces the underlying mathematical terms for those who want a mathematical foundation of the analytics methods. This book is one of a kind as it provides state of the art in advanced data analytics methods with important best practices to ensure the reader's success in data analytics.

Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Download or read book Big Data Analytics Methods written by Peter Ghavami and published by Createspace Independent Publishing Platform. This book was released on 2016-03-06 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensemble of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods are covered. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. This book is ideal as a text book for a course or as a reference for data scientists, data engineers, data analysts, Business intelligence practitioners, and business managers. It covers 10 chapters that discuss natural language processing (NLP), data visualization, prediction, optimization, artificial intelligence, regression analysis, cox hazard model and many analytics use case examples with applications in healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services. Big Data Analytics Methods Is a must read for those who wish to gain confidence and knowledge about big data and advanced analytics techniques. Read this book and confidently speak, lead and guide others about machine learning, neural networks, NLP, deep learning, and over 100 other analytics techniques. This book is fun and easy to read. It starts with simple and broad explanation of methods and gradually introduces more technical terms and techniques layer by layer. It finally introduces the underlying mathematical terms for those who want a mathematical foundation of the analytics methods. This book is one of a kind as it provides state of the art in advanced data analytics methods with important best practices to ensure the reader's success in data analytics.

Big Data

Author: Kuan-Ching Li

Publisher: CRC Press

Published: 2015-02-23

Total Pages: 498

ISBN-13: 1482240564

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As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre

Book Synopsis Big Data by : Kuan-Ching Li

Download or read book Big Data written by Kuan-Ching Li and published by CRC Press. This book was released on 2015-02-23 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre

Practical Big Data Analytics

Author: Nataraj Dasgupta

Publisher: Packt Publishing Ltd

Published: 2018-01-15

Total Pages: 402

ISBN-13: 1783554401

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Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

Book Synopsis Practical Big Data Analytics by : Nataraj Dasgupta

Download or read book Practical Big Data Analytics written by Nataraj Dasgupta and published by Packt Publishing Ltd. This book was released on 2018-01-15 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

Data Science and Big Data Analytics

Author: EMC Education Services

Publisher: John Wiley & Sons

Published: 2015-01-05

Total Pages: 432

ISBN-13: 1118876059

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Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Book Synopsis Data Science and Big Data Analytics by : EMC Education Services

Download or read book Data Science and Big Data Analytics written by EMC Education Services and published by John Wiley & Sons. This book was released on 2015-01-05 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Big Data Analytics

Author: David Loshin

Publisher: Elsevier

Published: 2013-08-23

Total Pages: 143

ISBN-13: 0124186645

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Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem

Book Synopsis Big Data Analytics by : David Loshin

Download or read book Big Data Analytics written by David Loshin and published by Elsevier. This book was released on 2013-08-23 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem

Big Data Analytics Methods

Author: Peter Ghavami

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2019-12-16

Total Pages: 282

ISBN-13: 1547401583

DOWNLOAD EBOOK

Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Predictive Analytics, Data Mining and Big Data

Author: S. Finlay

Publisher: Springer

Published: 2014-07-01

Total Pages: 241

ISBN-13: 1137379286

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This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.

Book Synopsis Predictive Analytics, Data Mining and Big Data by : S. Finlay

Download or read book Predictive Analytics, Data Mining and Big Data written by S. Finlay and published by Springer. This book was released on 2014-07-01 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.