Neural Network Modeling Using Sas Enterprise Miner

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Neural Network Modeling Using SAS Enterprise Miner

Author : Randall Matignon
Publisher : AuthorHouse
ISBN 13 : 1418423416
Total Pages : 608 pages
Book Rating : 4.4/5 (184 download)

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Book Synopsis Neural Network Modeling Using SAS Enterprise Miner by : Randall Matignon

Download or read book Neural Network Modeling Using SAS Enterprise Miner written by Randall Matignon and published by AuthorHouse. This book was released on 2005-08 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed in making statisticians, researchers, and programmers aware of the awesome new product now available in SAS called Enterprise Miner. The book will also make readers get familiar with the neural network forecasting methodology in statistics. One of the goals to this book is making the powerful new SAS module called Enterprise Miner easy for you to use with step-by-step instructions in creating a Enterprise Miner process flow diagram in preparation to data-mining analysis and neural network forecast modeling. Topics discussed in this book An overview to traditional regression modeling. An overview to neural network modeling. Numerical examples of various neural network designs and optimization techniques. An overview to the powerful SAS product called Enterprise Miner. An overview to the SAS neural network modeling procedure called PROC NEURAL. Designing a SAS Enterprise Miner process flow diagram to perform neural network forecast modeling and traditional regression modeling with an explanation to the various configuration settings to the Enterprise Miner nodes used in the analysis. Comparing neural network forecast modeling estimates with traditional modeling estimates based on various examples from SAS manuals and literature with an added overview to the various modeling designs and a brief explanation to the SAS modeling procedures, option statements, and corresponding SAS output listings.

Predictive Modeling with SAS Enterprise Miner

Author : Kattamuri S. Sarma
Publisher : SAS Institute
ISBN 13 : 163526040X
Total Pages : 574 pages
Book Rating : 4.6/5 (352 download)

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Book Synopsis Predictive Modeling with SAS Enterprise Miner by : Kattamuri S. Sarma

Download or read book Predictive Modeling with SAS Enterprise Miner written by Kattamuri S. Sarma and published by SAS Institute. This book was released on 2017-07-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: « Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--

Neural Network Models Using SAS Enterprise Miner

Author : Diana Abdul Wahab
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (969 download)

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Book Synopsis Neural Network Models Using SAS Enterprise Miner by : Diana Abdul Wahab

Download or read book Neural Network Models Using SAS Enterprise Miner written by Diana Abdul Wahab and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Networks with SAS Enterprise Miner

Author : Scientific Books
Publisher : CreateSpace
ISBN 13 : 9781514652282
Total Pages : 292 pages
Book Rating : 4.6/5 (522 download)

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Book Synopsis Neural Networks with SAS Enterprise Miner by : Scientific Books

Download or read book Neural Networks with SAS Enterprise Miner written by Scientific Books and published by CreateSpace. This book was released on 2015-06-22 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused in Neural Networks models. SAS Institute defines the concept of Data Mining as the process of selecting (Selecting), explore (Exploring), modify (Modifying), modeling (Modeling) and rating (Assessment) large amounts of data with the aim of uncovering unknown patterns which can be used as a comparative advantage with respect to competitors. This process is summarized with the acronym SEMMA which are the initials of the 5 phases which comprise the process of Data Mining according to SAS Institute.

Data Mining Using SAS Enterprise Miner

Author : Randall Matignon
Publisher : John Wiley & Sons
ISBN 13 : 0470149019
Total Pages : 584 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Data Mining Using SAS Enterprise Miner by : Randall Matignon

Download or read book Data Mining Using SAS Enterprise Miner written by Randall Matignon and published by John Wiley & Sons. This book was released on 2007-08-03 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is a part of the Enterprise Miner software with regard to SEMMA design and data mining analysis. Data Mining Using SAS Enterprise Miner introduces readers to a wide variety of data mining techniques and explains the purpose of-and reasoning behind-every node that is a part of the Enterprise Miner software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes in SAS Enterprise Miner v4.3, followed by detailed explanations of configuration settings that are located within each node. Features of the book include: The exploration of node relationships and patterns using data from an assortment of computations, charts, and graphs commonly used in SAS procedures A step-by-step approach to each node discussion, along with an assortment of illustrations that acquaint the reader with the SAS Enterprise Miner working environment Descriptive detail of the powerful Score node and associated SAS code, which showcases the important of managing, editing, executing, and creating custom-designed Score code for the benefit of fair and comprehensive business decision-making Complete coverage of the wide variety of statistical techniques that can be performed using the SEMMA nodes An accompanying Web site that provides downloadable Score code, training code, and data sets for further implementation, manipulation, and interpretation as well as SAS/IML software programming code This book is a well-crafted study guide on the various methods employed to randomly sample, partition, graph, transform, filter, impute, replace, cluster, and process data as well as interactively group and iteratively process data while performing a wide variety of modeling techniques within the process flow of the SAS Enterprise Miner software. Data Mining Using SAS Enterprise Miner is suitable as a supplemental text for advanced undergraduate and graduate students of statistics and computer science and is also an invaluable, all-encompassing guide to data mining for novice statisticians and experts alike.

Data Mining Techniques. Predictive Models with SAS Enterprise Miner

Author : Scientific Books
Publisher : CreateSpace
ISBN 13 : 9781512100037
Total Pages : 332 pages
Book Rating : 4.1/5 ( download)

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Book Synopsis Data Mining Techniques. Predictive Models with SAS Enterprise Miner by : Scientific Books

Download or read book Data Mining Techniques. Predictive Models with SAS Enterprise Miner written by Scientific Books and published by CreateSpace. This book was released on 2015-05-08 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused predictive models. SAS Institute defines the concept of Data Mining as the process of selecting (Selecting), explore (Exploring), modify (Modifying), modeling (Modeling) and rating (Assessment) large amounts of data with the aim of uncovering unknown patterns which can be used as a comparative advantage with respect to competitors. This process is summarized with the acronym SEMMA which are the initials of the 5 phases which comprise the process of Data Mining according to SAS Institute. The essential content of the book is as follows: SAS ENTERPRISE MINER WORKING ENVIRONMENT MODELLING PREDICTIVE TECHNIQUES WITH SAS ENTERPRISE MINER REGRESSION NODE: MULTIPLE REGRESSION MODEL LOGISTIC REGRESSION DMINE REGRESSION NODE PARTIAL LEAST SQUARES NODE. PLS REGRESSION LARS NODE CLASSIFICATION PREDICTIVE TECHNIQUES. DECISION TREES WITH SAS ENTERPRISE MINER DECISION TREE NODE PREDICTIVE MODELS WITH NEURAL NETWORKS WITH SAS ENTERPRISE MINER OPTIMIZATION AND ADJUSTMENT OF MODELS WITH NETS: NEURAL NETWORK NODE SIMPLE NEURAL NETWORKS PERCEPTRONS HIDDEN LAYERS MULTILAYER PERCEPTRONS (MLPS) RADIAL BASIS FUNCTION (RBF) NETWORKS SCORING AUTONEURAL NODE NETWORK ARCHITECTURES NEURAL NODE TWOSTAGE NODE GRADIENT BOOSTING NODE MEMORY-BASED REASONING (MBR) NODE RULE INDUCTION NODE ENSEMBLE NODE COMBINING MODELS USING THE ENSEMBLE NODE MODEL IMPORT NODE SVM NODE ASSESS PHASE IN DATA MINING PROCESS CUTOFF NODE DECISIONS NODE MODEL COMPARISON NODE SCORE NODE

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

Author : Olivia Parr-Rud
Publisher : SAS Institute
ISBN 13 : 1629593273
Total Pages : 182 pages
Book Rating : 4.6/5 (295 download)

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Book Synopsis Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner by : Olivia Parr-Rud

Download or read book Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner written by Olivia Parr-Rud and published by SAS Institute. This book was released on 2014-10 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. --

Predictive Modeling with SAS Enterprise Miner

Author : Kattamuri S. Sarma
Publisher : SAS Institute
ISBN 13 : 1635260388
Total Pages : 574 pages
Book Rating : 4.6/5 (352 download)

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Book Synopsis Predictive Modeling with SAS Enterprise Miner by : Kattamuri S. Sarma

Download or read book Predictive Modeling with SAS Enterprise Miner written by Kattamuri S. Sarma and published by SAS Institute. This book was released on 2017-07-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step guide to predictive modeling! Kattamuri Sarma's Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third Edition, will show you how to develop and test predictive models quickly using SAS Enterprise Miner. Using realistic data, the book explains complex methods in a simple and practical way to readers from different backgrounds and industries. Incorporating the latest version of Enterprise Miner, this third edition also expands the section on time series. Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. Topics covered include logistic regression, regression, decision trees, neural networks, variable clustering, observation clustering, data imputation, binning, data exploration, variable selection, variable transformation, and much more, including analysis of textual data. Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner!

Data Mining With SAS Enterprise Miner. Predictive Techniques

Author : C. Perez
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781978373624
Total Pages : 268 pages
Book Rating : 4.3/5 (736 download)

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Book Synopsis Data Mining With SAS Enterprise Miner. Predictive Techniques by : C. Perez

Download or read book Data Mining With SAS Enterprise Miner. Predictive Techniques written by C. Perez and published by Createspace Independent Publishing Platform. This book was released on 2017-10-17 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential aim of this book is to use predictive models for Data Mning. Models of decision trees, regression and neural networks are used to predict various categories. This book shows you how to build decision tree models to predict a categorical target and how to build regression tree models and neural network models to predict a continuous target. Successive chapters present examples that clarify the application of the models in the field of Data Mining. The examples are solved step by step with SAS Enterprise Miner in order to make easier the understanding of the methodologies used. The book begins by introducing the basics of creating a project, manipulating data sources, and navigating through different results windows. Data Miming tools are used to build the main models: Decision Tree, Neural Network, and Regression. These are addressed in considerable detail, with numerous examples of practical business applications that are illustrated with tables, charts, displays, equations, and even manual calculations that let you see the essence of what Enterprise Miner is doing when it estimates or optimizes a given model.

Data Mining Techniques. Segmentation with SAS Enterprise Miner

Author : Scientific Books
Publisher : CreateSpace
ISBN 13 : 9781512098006
Total Pages : 288 pages
Book Rating : 4.0/5 (98 download)

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Book Synopsis Data Mining Techniques. Segmentation with SAS Enterprise Miner by : Scientific Books

Download or read book Data Mining Techniques. Segmentation with SAS Enterprise Miner written by Scientific Books and published by CreateSpace. This book was released on 2015-05-08 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused segmentation tasks. SAS Institute defines the concept of Data Mining as the process of selecting (Selecting), explore (Exploring), modify (Modifying), modeling (Modeling) and rating (Assessment) large amounts of data with the aim of uncovering unknown patterns which can be used as a comparative advantage with respect to competitors. This process is summarized with the acronym SEMMA which are the initials of the 5 phases which comprise the process of Data Mining according to SAS Institute. The essential content of the book is as follows: SAS ENTERPRISE MINER WORKING ENVIRONMENTSEGMENTATION PREDICTIVE TECHNIQUES MODELING PREDICTIVE TECHNIQUES FOR SEGMENTATION REGRESSION NODE: MULTIPLE REGRESSION MODEL LOGISTIC REGRESSION DMINE REGRESSION NODE SEGMENTATION PREDICTIVE TECHNIQUES. DECISION TREES DECISION TREE NODE DECISION TREE INTERACTIVE TRAINING DECISION TREE NODE OUTPUT DATA SOURCES GRADIENT BOOSTING NODE SEGMENTATION PREDICITIVE MODELS WITH NEURAL NETWORKS NEURAL NETWORKS FOR SEGMENTATION OPTIMIZATION AND ADJUSTMENT OF SEGMENTATION MODELS WITH NETS: NEURAL NETWORK NODE SIMPLE NEURAL NETWORKS PERCEPTRONS HIDDEN LAYERS MULTILAYER PERCEPTRONS (MLPS) RADIAL BASIS FUNCTION (RBF) NETWORKS LOCAL PROCESSING NETWORKS SCORING NEURAL NETWORK NODE TRAIN PROPERTIES NEURAL NETWORK NODE RESULTS AUTONEURAL NODE NETWORK ARCHITECTURES DM NEURAL NODE ENSEMBLE NODE SEGMENTATION DESCRIPTIVE TECHNIQUES. CLUSTER ANALYSIS CLUSTER ANALYSIS ON ENTERPRISE MINER CLUSTER NODE SOM/KOHONEN NODE VARIABLE CLUSTERING NODE PREDICTIVE MODELING WITH VARIABLE CLUSTERING EXAMPLE ASSESS PHASE IN SEGMENTATION PREDICTIVE MODELS CUTOFF NODE SCORE NODE SEGMENT PROFILE NODE

Data Mining Using SAS Applications

Author : George Fernandez
Publisher : CRC Press
ISBN 13 : 9781420057331
Total Pages : 536 pages
Book Rating : 4.0/5 (573 download)

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Book Synopsis Data Mining Using SAS Applications by : George Fernandez

Download or read book Data Mining Using SAS Applications written by George Fernandez and published by CRC Press. This book was released on 2010-12-12 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods stress the use of visualization to thoroughly study the structure of data and check the validity of statistical models fitted to data. Learn how to convert PC databases to SAS data Discover sampling techniques to create training and validation samples Understand frequency data analysis for categorical data Explore supervised and unsupervised learning Master exploratory graphical techniques Acquire model validation techniques in regression and classification The text furnishes 13 easy-to-use SAS data mining macros designed to work with the standard SAS modules. No additional modules or previous experience in SAS programming is required. The author shows how to perform complete predictive modeling, including data exploration, model fitting, assumption checks, validation, and scoring new data, on SAS datasets in less than ten minutes!

Applied Health Analytics and Informatics Using SAS

Author : Joseph M. Woodside
Publisher : SAS Institute
ISBN 13 : 1635266149
Total Pages : 429 pages
Book Rating : 4.6/5 (352 download)

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Book Synopsis Applied Health Analytics and Informatics Using SAS by : Joseph M. Woodside

Download or read book Applied Health Analytics and Informatics Using SAS written by Joseph M. Woodside and published by SAS Institute. This book was released on 2018-11-08 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage health data into insight! Applied Health Analytics and Informatics Using SAS describes health anamatics, a result of the intersection of data analytics and health informatics. Healthcare systems generate nearly a third of the world’s data, and analytics can help to eliminate medical errors, reduce readmissions, provide evidence-based care, demonstrate quality outcomes, and add cost-efficient care. This comprehensive textbook includes data analytics and health informatics concepts, along with applied experiential learning exercises and case studies using SAS Enterprise MinerTM within the healthcare industry setting. Topics covered include: Sampling and modeling health data – both structured and unstructured Exploring health data quality Developing health administration and health data assessment procedures Identifying future health trends Analyzing high-performance health data mining models Applied Health Analytics and Informatics Using SAS is intended for professionals, lifelong learners, senior-level undergraduates, graduate-level students in professional development courses, health informatics courses, health analytics courses, and specialized industry track courses. This textbook is accessible to a wide variety of backgrounds and specialty areas, including administrators, clinicians, and executives. This book is part of the SAS Press program.

Data Science and Machine Learning for Non-Programmers

Author : Dothang Truong
Publisher : CRC Press
ISBN 13 : 1003835635
Total Pages : 768 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Data Science and Machine Learning for Non-Programmers by : Dothang Truong

Download or read book Data Science and Machine Learning for Non-Programmers written by Dothang Truong and published by CRC Press. This book was released on 2024-02-23 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively. Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders. Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.

Machine Learning with SAS Viya

Author : SAS Institute Inc.
Publisher : SAS Institute
ISBN 13 : 1951685377
Total Pages : 295 pages
Book Rating : 4.9/5 (516 download)

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Book Synopsis Machine Learning with SAS Viya by : SAS Institute Inc.

Download or read book Machine Learning with SAS Viya written by SAS Institute Inc. and published by SAS Institute. This book was released on 2020-05-29 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master machine learning with SAS Viya! Machine learning can feel intimidating for new practitioners. Machine Learning with SAS Viya provides everything you need to know to get started with machine learning in SAS Viya, including decision trees, neural networks, and support vector machines. The analytics life cycle is covered from data preparation and discovery to deployment. Working with open-source code? Machine Learning with SAS Viya has you covered – step-by-step instructions are given on how to use SAS Model Manager tools with open source. SAS Model Studio features are highlighted to show how to carry out machine learning in SAS Viya. Demonstrations, practice tasks, and quizzes are included to help sharpen your skills. In this book, you will learn about: Supervised and unsupervised machine learning Data preparation and dealing with missing and unstructured data Model building and selection Improving and optimizing models Model deployment and monitoring performance

PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS. REGRESSION AND DECISION TREES

Author :
Publisher : CESAR PEREZ
ISBN 13 : 100897952X
Total Pages : 222 pages
Book Rating : 4.0/5 (89 download)

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Book Synopsis PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS. REGRESSION AND DECISION TREES by :

Download or read book PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS. REGRESSION AND DECISION TREES written by and published by CESAR PEREZ. This book was released on with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential aim of this book is to use predictive models to analyze risk. Models of decision trees, regression and neural networks are used to predict various risk categories. This book shows you how to build decision tree models to predict a categorical target and how to build regression tree models and neural network models to predict a continuous target. Successive chapters present examples that clarify the application of the models in the field of risk. The examples are solved step by step with SAS Enterprise Miner in order to make easier the understanding of the methodologies used. The book begins by introducing the basics of creating a project, manipulating data sources, and navigating through different results windows. Data Mining tools are used to build the main risk models: Decision Tree, Neural Network, and Regression.

Decision Trees for Analytics Using SAS Enterprise Miner

Author : Barry De Ville
Publisher :
ISBN 13 : 9781642953138
Total Pages : 268 pages
Book Rating : 4.9/5 (531 download)

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Book Synopsis Decision Trees for Analytics Using SAS Enterprise Miner by : Barry De Ville

Download or read book Decision Trees for Analytics Using SAS Enterprise Miner written by Barry De Ville and published by . This book was released on 2019-07-03 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision Trees for Analytics Using SAS Enterprise Miner is the most comprehensive treatment of decision tree theory, use, and applications available in one easy-to-access place. This book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression, as well as other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes. An expanded and enhanced release of Decision Trees for Business Intelligence and Data Mining Using SAS Enterprise Miner, this book adds up-to-date treatments of boosting and high-performance forest approaches and rule induction. There is a dedicated section on the most recent findings related to bias reduction in variable selection. It provides an exhaustive treatment of the end-to-end process of decision tree construction and the respective considerations and algorithms, and it includes discussions of key issues in decision tree practice. Analysts who have an introductory understanding of data mining and who are looking for a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining will benefit from this book.

Data Science and Machine Learning for Non-Programmers

Author : Dothang Truong
Publisher : CRC Press
ISBN 13 : 1003835619
Total Pages : 590 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Data Science and Machine Learning for Non-Programmers by : Dothang Truong

Download or read book Data Science and Machine Learning for Non-Programmers written by Dothang Truong and published by CRC Press. This book was released on 2024-02-23 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively. Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders. Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.