Relational Analytics

Relational Analytics

Author: Jody Hoffer Gittell

Publisher: Routledge

Published: 2021-06-13

Total Pages: 196

ISBN-13: 1000391639

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This guidebook goes beyond people analytics to provide a research-based, practice-tested methodology for doing relational analytics, based on the science of relational coordination. We are witnessing a revolution in people analytics, where data are used to identify and leverage human talent to drive performance outcomes. Today’s workplace is interdependent, however, and individuals drive performance through networks that span department, organization and sector boundaries. This book shares the relational coordination framework, with a validated scalable analytic tool that has been used successfully across dozens of countries and industries to understand, measure and influence networks of relationships in and across organizations, and which can be applied at any level in the private and public sectors worldwide. Graduate students and practitioners in human resource management, health policy and management, organizational behavior, engineering and network analysis will appreciate the methodology and hands-on guidance this book provides, with its focus on identifying, analyzing and building networks of productive interdependence. Online resources include data appendices and statistical commands that can be used to conduct all these analyses in readers’ own organizations.


Book Synopsis Relational Analytics by : Jody Hoffer Gittell

Download or read book Relational Analytics written by Jody Hoffer Gittell and published by Routledge. This book was released on 2021-06-13 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guidebook goes beyond people analytics to provide a research-based, practice-tested methodology for doing relational analytics, based on the science of relational coordination. We are witnessing a revolution in people analytics, where data are used to identify and leverage human talent to drive performance outcomes. Today’s workplace is interdependent, however, and individuals drive performance through networks that span department, organization and sector boundaries. This book shares the relational coordination framework, with a validated scalable analytic tool that has been used successfully across dozens of countries and industries to understand, measure and influence networks of relationships in and across organizations, and which can be applied at any level in the private and public sectors worldwide. Graduate students and practitioners in human resource management, health policy and management, organizational behavior, engineering and network analysis will appreciate the methodology and hands-on guidance this book provides, with its focus on identifying, analyzing and building networks of productive interdependence. Online resources include data appendices and statistical commands that can be used to conduct all these analyses in readers’ own organizations.

R for Data Science

R for Data Science

Author: Hadley Wickham

Publisher: "O'Reilly Media, Inc."

Published: 2016-12-12

Total Pages: 521

ISBN-13: 1491910364

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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


Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Linked Open Data -- Creating Knowledge Out of Interlinked Data

Linked Open Data -- Creating Knowledge Out of Interlinked Data

Author: Sören Auer

Publisher: Springer

Published: 2014-07-31

Total Pages: 218

ISBN-13: 3319098462

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Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.


Book Synopsis Linked Open Data -- Creating Knowledge Out of Interlinked Data by : Sören Auer

Download or read book Linked Open Data -- Creating Knowledge Out of Interlinked Data written by Sören Auer and published by Springer. This book was released on 2014-07-31 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.

The Relational Lens

The Relational Lens

Author: John Ashcroft

Publisher: Cambridge University Press

Published: 2016-10-19

Total Pages: 253

ISBN-13: 1108108024

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Drawing on the authors' combined years of experience in both private and public-sector organisations, this practical book highlights the importance of relationship building between individuals, groups and organisations in diverse contexts. It will make a valuable read for business professionals and graduate students in fields as varied as change management, leadership, organisational psychology, and organisational behaviour. Employing the Relational Proximity® framework, it provides tools for informing assessment of the relational impact of policy and management decisions, enabling evaluation of organisational relationships, providing a language for constructive discussion of strained relationships, and integrating a range of models and perspectives within one process. Using real-world case studies and models, the conditions within which people are more likely to form and conduct effective relationships are also examined. This combined approach provides the language and concepts to enable constructive discussion and actionable solutions in building trust and sustainable value.


Book Synopsis The Relational Lens by : John Ashcroft

Download or read book The Relational Lens written by John Ashcroft and published by Cambridge University Press. This book was released on 2016-10-19 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on the authors' combined years of experience in both private and public-sector organisations, this practical book highlights the importance of relationship building between individuals, groups and organisations in diverse contexts. It will make a valuable read for business professionals and graduate students in fields as varied as change management, leadership, organisational psychology, and organisational behaviour. Employing the Relational Proximity® framework, it provides tools for informing assessment of the relational impact of policy and management decisions, enabling evaluation of organisational relationships, providing a language for constructive discussion of strained relationships, and integrating a range of models and perspectives within one process. Using real-world case studies and models, the conditions within which people are more likely to form and conduct effective relationships are also examined. This combined approach provides the language and concepts to enable constructive discussion and actionable solutions in building trust and sustainable value.

Beginning Relational Data Modeling

Beginning Relational Data Modeling

Author: Sharon Allen

Publisher:

Published: 2005-03-24

Total Pages: 646

ISBN-13:

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*Immediately accessible to anyone who must design a relational data model—regardless of prior experience *Concise, straightforward explanations to a usually complex/ jargon-rich discipline *Examples are based on extensive author experience modeling for real business systems


Book Synopsis Beginning Relational Data Modeling by : Sharon Allen

Download or read book Beginning Relational Data Modeling written by Sharon Allen and published by . This book was released on 2005-03-24 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: *Immediately accessible to anyone who must design a relational data model—regardless of prior experience *Concise, straightforward explanations to a usually complex/ jargon-rich discipline *Examples are based on extensive author experience modeling for real business systems

Relational Data Mining

Relational Data Mining

Author: Saso Dzeroski

Publisher: Springer Science & Business Media

Published: 2001-08

Total Pages: 422

ISBN-13: 9783540422891

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As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.


Book Synopsis Relational Data Mining by : Saso Dzeroski

Download or read book Relational Data Mining written by Saso Dzeroski and published by Springer Science & Business Media. This book was released on 2001-08 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.

SQL for Data Science

SQL for Data Science

Author: Antonio Badia

Publisher: Springer Nature

Published: 2020-11-09

Total Pages: 290

ISBN-13: 3030575926

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This textbook explains SQL within the context of data science and introduces the different parts of SQL as they are needed for the tasks usually carried out during data analysis. Using the framework of the data life cycle, it focuses on the steps that are very often given the short shift in traditional textbooks, like data loading, cleaning and pre-processing. The book is organized as follows. Chapter 1 describes the data life cycle, i.e. the sequence of stages from data acquisition to archiving, that data goes through as it is prepared and then actually analyzed, together with the different activities that take place at each stage. Chapter 2 gets into databases proper, explaining how relational databases organize data. Non-traditional data, like XML and text, are also covered. Chapter 3 introduces SQL queries, but unlike traditional textbooks, queries and their parts are described around typical data analysis tasks like data exploration, cleaning and transformation. Chapter 4 introduces some basic techniques for data analysis and shows how SQL can be used for some simple analyses without too much complication. Chapter 5 introduces additional SQL constructs that are important in a variety of situations and thus completes the coverage of SQL queries. Lastly, chapter 6 briefly explains how to use SQL from within R and from within Python programs. It focuses on how these languages can interact with a database, and how what has been learned about SQL can be leveraged to make life easier when using R or Python. All chapters contain a lot of examples and exercises on the way, and readers are encouraged to install the two open-source database systems (MySQL and Postgres) that are used throughout the book in order to practice and work on the exercises, because simply reading the book is much less useful than actually using it. This book is for anyone interested in data science and/or databases. It just demands a bit of computer fluency, but no specific background on databases or data analysis. All concepts are introduced intuitively and with a minimum of specialized jargon. After going through this book, readers should be able to profitably learn more about data mining, machine learning, and database management from more advanced textbooks and courses.


Book Synopsis SQL for Data Science by : Antonio Badia

Download or read book SQL for Data Science written by Antonio Badia and published by Springer Nature. This book was released on 2020-11-09 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook explains SQL within the context of data science and introduces the different parts of SQL as they are needed for the tasks usually carried out during data analysis. Using the framework of the data life cycle, it focuses on the steps that are very often given the short shift in traditional textbooks, like data loading, cleaning and pre-processing. The book is organized as follows. Chapter 1 describes the data life cycle, i.e. the sequence of stages from data acquisition to archiving, that data goes through as it is prepared and then actually analyzed, together with the different activities that take place at each stage. Chapter 2 gets into databases proper, explaining how relational databases organize data. Non-traditional data, like XML and text, are also covered. Chapter 3 introduces SQL queries, but unlike traditional textbooks, queries and their parts are described around typical data analysis tasks like data exploration, cleaning and transformation. Chapter 4 introduces some basic techniques for data analysis and shows how SQL can be used for some simple analyses without too much complication. Chapter 5 introduces additional SQL constructs that are important in a variety of situations and thus completes the coverage of SQL queries. Lastly, chapter 6 briefly explains how to use SQL from within R and from within Python programs. It focuses on how these languages can interact with a database, and how what has been learned about SQL can be leveraged to make life easier when using R or Python. All chapters contain a lot of examples and exercises on the way, and readers are encouraged to install the two open-source database systems (MySQL and Postgres) that are used throughout the book in order to practice and work on the exercises, because simply reading the book is much less useful than actually using it. This book is for anyone interested in data science and/or databases. It just demands a bit of computer fluency, but no specific background on databases or data analysis. All concepts are introduced intuitively and with a minimum of specialized jargon. After going through this book, readers should be able to profitably learn more about data mining, machine learning, and database management from more advanced textbooks and courses.

International Pecking Orders

International Pecking Orders

Author: Vincent Pouliot

Publisher: Cambridge University Press

Published: 2016-03-10

Total Pages: 355

ISBN-13: 1107143438

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This book examines the establishment of international hierarchies in multilateral diplomacy. Vincent Pouliot observes that in any multilateral setting, some state representatives weigh much more heavily than others, and argues that the practice of diplomacy is structured by a largely unspoken hierarchy of standing, which practitioners refer to as the 'pecking order'.


Book Synopsis International Pecking Orders by : Vincent Pouliot

Download or read book International Pecking Orders written by Vincent Pouliot and published by Cambridge University Press. This book was released on 2016-03-10 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the establishment of international hierarchies in multilateral diplomacy. Vincent Pouliot observes that in any multilateral setting, some state representatives weigh much more heavily than others, and argues that the practice of diplomacy is structured by a largely unspoken hierarchy of standing, which practitioners refer to as the 'pecking order'.

Data and Analytics in Accounting

Data and Analytics in Accounting

Author: Ann C. Dzuranin

Publisher: Wiley Global Education

Published: 2022-12-02

Total Pages: 659

ISBN-13: 1119807123

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Develop an integrated data analysis and critical thinking skill set needed to be successful in the rapidly changing accounting profession. Data Analytics in Accounting: An Integrated Approach, 1st Edition helps students develop the professional skills you need to plan, perform, and communicate data analyses effectively and efficiently in the real world. An integrated approach provides flexibility for use within a standalone course or across the accounting curriculum.


Book Synopsis Data and Analytics in Accounting by : Ann C. Dzuranin

Download or read book Data and Analytics in Accounting written by Ann C. Dzuranin and published by Wiley Global Education. This book was released on 2022-12-02 with total page 659 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop an integrated data analysis and critical thinking skill set needed to be successful in the rapidly changing accounting profession. Data Analytics in Accounting: An Integrated Approach, 1st Edition helps students develop the professional skills you need to plan, perform, and communicate data analyses effectively and efficiently in the real world. An integrated approach provides flexibility for use within a standalone course or across the accounting curriculum.

SQL Engines for Big Data Analytics

SQL Engines for Big Data Analytics

Author: Ajit Singh

Publisher: GRIN Verlag

Published: 2019-12-09

Total Pages: 60

ISBN-13: 3346079090

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Master's Thesis from the year 2018 in the subject Computer Science - Internet, New Technologies, grade: 8, , course: Master of Computer Application, language: English, abstract: This book aims to describe how data analytics works for big data and how they are used in business. It gives an overview of existing technologies and ap-proaches to building data analytics infrastructures. It also defines points that should be taken into consideration while choosing the most suitable software solution for a particular use case. The research is done by studying architectural principles of big data sys-tems and investigating the market of data analytics software. The result of this work is a composite report including comparison of several technologies and a list of criteria considered. The final report can be used as a guideline for choosing the most suitable technology for implementing an analytical platform in a broad variety of organizations. With a growing amount of data generated, their changing and evolving, the concept of big data has become incredibly popular in last years. It provides a set of new approaches and techniques allowing to work e ciently with huge volumes of records. Nowadays, information is one of the most important resources; it can help with decision making and business processes optimization. However, to get actual insights and unlock a potential of data, it is necessary to process them and discover the information hidden inside it which is a goal of data analytics. Data analytic platforms allow to manipulate with raw data in order to find out what exactly they contain. These systems are complex and includes multiple components therefore their designing requires comprehensive analysis of available options.


Book Synopsis SQL Engines for Big Data Analytics by : Ajit Singh

Download or read book SQL Engines for Big Data Analytics written by Ajit Singh and published by GRIN Verlag. This book was released on 2019-12-09 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2018 in the subject Computer Science - Internet, New Technologies, grade: 8, , course: Master of Computer Application, language: English, abstract: This book aims to describe how data analytics works for big data and how they are used in business. It gives an overview of existing technologies and ap-proaches to building data analytics infrastructures. It also defines points that should be taken into consideration while choosing the most suitable software solution for a particular use case. The research is done by studying architectural principles of big data sys-tems and investigating the market of data analytics software. The result of this work is a composite report including comparison of several technologies and a list of criteria considered. The final report can be used as a guideline for choosing the most suitable technology for implementing an analytical platform in a broad variety of organizations. With a growing amount of data generated, their changing and evolving, the concept of big data has become incredibly popular in last years. It provides a set of new approaches and techniques allowing to work e ciently with huge volumes of records. Nowadays, information is one of the most important resources; it can help with decision making and business processes optimization. However, to get actual insights and unlock a potential of data, it is necessary to process them and discover the information hidden inside it which is a goal of data analytics. Data analytic platforms allow to manipulate with raw data in order to find out what exactly they contain. These systems are complex and includes multiple components therefore their designing requires comprehensive analysis of available options.