Download or read book Essentials of Modeling and Analytics written by David B. Speights and published by Routledge. This book was released on 2017-09-11 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Modeling and Analytics illustrates how and why analytics can be used effectively by loss prevention staff. The book offers an in-depth overview of analytics, first illustrating how analytics are used to solve business problems, then exploring the tools and training that staff will need in order to engage solutions. The text also covers big data analytical tools and discusses if and when they are right for retail loss prevention professionals, and illustrates how to use analytics to test the effectiveness of loss prevention initiatives. Ideal for loss prevention personnel on all levels, this book can also be used for loss prevention analytics courses. Essentials of Modeling and Analytics was named one of the best Analytics books of all time by BookAuthority, one of the world's leading independent sites for nonfiction book recommendations.

Download or read book Data Modeling Essentials written by Graeme Simsion and published by Elsevier. This book was released on 2004-12-03 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with "the rules". In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. - Thorough coverage of the fundamentals and relevant theory - Recognition and support for the creative side of the process - Expanded coverage of applied data modeling includes new chapters on logical and physical database design - New material describing a powerful technique for model verification - Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict

Download or read book Essentials of Structural Equation Modeling written by Mustafa Emre Civelek and published by Lulu.com. This book was released on 2018-03-12 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. Many universities do not include this method in the curriculum, so students and scholars try to solve these problems using books and internet resources. This book aims to guide the researcher in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling practically. For students writing theses and scholars preparing academic articles, this book aims to analyze systematically the methodology of studies conducted using structural equation modeling methods in the social sciences. In as simple language as possible, it conveys basic information. It consists of two parts: the first gives basic concepts of structural equation modeling, and the second gives examples of applications.

Download or read book Fundamentals of Machine Learning for Predictive Data Analytics second edition written by John D. Kelleher and published by MIT Press. This book was released on 2020-10-20 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

Download or read book Essential Business Process Modeling written by Michael Havey and published by "O'Reilly Media, Inc.". This book was released on 2005-08-18 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ten years ago, groupware bundled with email and calendar applications helped track the flow of work from person to person within an organization. Workflow in today's enterprise means more monitoring and orchestrating massive systems. A new technology called Business Process Management, or BPM, helps software architects and developers design, code, run, administer, and monitor complex network-based business processes BPM replaces those sketchy flowchart diagrams that business analysts draw on whiteboards with a precise model that uses standard graphical and XML representations, and an architecture that allows it converse with other services, systems, and users. Sound complicated? It is. But it's downright frustrating when you have to search the Web for every little piece of information vital to the process. Essential Business Process Modeling gathers all the concepts, design, architecture, and standard specifications of BPM into one concise book, and offers hands-on examples that illustrate BPM's approach to process notation, execution, administration and monitoring. Author Mike Havey demonstrates standard ways to code rigorous processes that are centerpieces of a service-oriented architecture (SOA), which defines how networks interact so that one can perform a service for the other. His book also shows how BPM complements enterprise application integration (EAI), a method for moving from older applications to new ones, and Enterprise Service BUS for integrating different web services, messaging, and XML technologies into a single network. BPM, he says, is to this collection of services what a conductor is to musicians in an orchestra: it coordinates their actions in the performance of a larger composition. Essential Business Process Modeling teaches you how to develop examples of process-oriented applications using free tools that can be run on an average PC or laptop. You'll also learn about BPM design patterns and best practices, as well as some underlying theory. The best way to monitor processes within an enterprise is with BPM, and the best way to navigate BPM is with this valuable book.

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

Download or read book Business Modeling and Data Mining written by Dorian Pyle and published by Elsevier. This book was released on 2003-05-17 with total page 721 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem. This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations. · Teaches how to discover, construct and refine models that are useful in business situations· Teaches how to design, discover and develop the data necessary for mining · Provides a practical approach to mining data for all business situations· Provides a comprehensive, easy-to-use, fully interactive methodology for building models and mining data· Provides pointers to supplemental online resources, including a downloadable version of the methodology and software tools.

Download or read book Mastering Data Modeling written by John Carlis and published by Addison-Wesley Professional. This book was released on 2000-11-10 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data modeling is one of the most critical phases in the database application development process, but also the phase most likely to fail. A master data modeler must come into any organization, understand its data requirements, and skillfully model the data for applications that most effectively serve organizational needs. Mastering Data Modeling is a complete guide to becoming a successful data modeler. Featuring a requirements-driven approach, this book clearly explains fundamental concepts, introduces a user-oriented data modeling notation, and describes a rigorous, step-by-step process for collecting, modeling, and documenting the kinds of data that users need. Assuming no prior knowledge, Mastering Data Modeling sets forth several fundamental problems of data modeling, such as reconciling the software developer's demand for rigor with the users' equally valid need to speak their own (sometimes vague) natural language. In addition, it describes the good habits that help you respond to these fundamental problems. With these good habits in mind, the book describes the Logical Data Structure (LDS) notation and the process of controlled evolution by which you can create low-cost, user-approved data models that resist premature obsolescence. Also included is an encyclopedic analysis of all data shapes that you will encounter. Most notably, the book describes The Flow, a loosely scripted process by which you and the users gradually but continuously improve an LDS until it faithfully represents the information needs. Essential implementation and technology issues are also covered. You will learn about such vital topics as: The fundamental problems of data modeling The good habits that help a data modeler be effective and economical LDS notation, which encourages these good habits How to read an LDS aloud--in declarative English sentences How to write a well-formed (syntactically correct) LDS How to get users to name the parts of an LDS with words from their own business vocabulary How to visualize data for an LDS A catalog of LDS shapes that recur throughout all data models The Flow--the template for your conversations with users How to document an LDS for users, data modelers, and technologists How to map an LDS to a relational schema How LDS differs from other notations and why "Story interludes" appear throughout the book, illustrating real-world successes of the LDS notation and controlled evolution process. Numerous exercises help you master critical skills. In addition, two detailed, annotated sample conversations with users show you the process of controlled evolution in action.

Download or read book Analytics in a Big Data World written by Bart Baesens and published by John Wiley & Sons. This book was released on 2014-04-15 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.

Download or read book Modeling with Data written by Ben Klemens and published by Princeton University Press. This book was released on 2008-10-06 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.

Download or read book Basics of Power BI Modeling written by Reza Rad and published by RADACAD Systems Limited. This book was released on 2020-09-11 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: I have been dealing with many Power BI challenges in my professional life as a Power BI consultant and a trainer. Challenges normally come as calculation or DAX questions, or sometimes as a performance question. However, after digging deeper into the problem, soon, it will be revealed that the problem is related to a more fundamental challenge; data modeling.If you have a Power BI implementation with many calculation-related or performance-related issues, I strongly suggest looking into your data model because that is where most of the problems start.A good data model is a great base, which upon that, you can build up many stories of calculations and analysis. A bad data model causes problems on every level that you add upon it, and might sometime cause the whole solution to collapse.Fortunately, data modeling is not rocket science. I explained the basic principles of the data modeling with examples in this book. Use this book as the learning path towards a better data model. Most of the tips mentioned in this book are product-agnostic (such as star-schema, dimension, and fact tables). However, this book is particularly designed and developed for a Power BI product user.This book is for you if you are building a Power BI solution. If your task is only visualizing the existing data, this book might not be needed for you. However, What I have seen in many cases, is that the requirement starts with just visualize the data, and then more data tables appear, and you get into the tunnel of data modeling without knowing the principles of it. This book is a guide for you through that tunnel.

Download or read book Basics of Structural Equation Modeling written by Geoffrey M. Maruyama and published by SAGE Publications. This book was released on 1997-09-22 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the availability of software programs such as LISREL, EQS, and AMOS modeling techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and for testing the plausibility of hypothesizing for a particular data set. The popularity of these techniques, however, has often led to misunderstandings of them, particularly by students being exposed to them for the first time. Through the use of careful narrative explanation, Basics of Structural Equation Modeling describes the logic underlying structural equation modeling (SEM) approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores the various methodologies for analyzing structural equation data.

Download or read book Handbook of Regression Modeling in People Analytics written by Keith McNulty and published by CRC Press. This book was released on 2021-07-29 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions. This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a ‘sweet spot’ where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers. Key Features: 16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing) Clear step-by-step instructions on executing the analyses Clear guidance on how to interpret results Primary instruction in R but added sections for Python coders Discussion exercises and data exercises for each of the main chapters Final chapter of practice material and datasets ideal for class homework or project work.

Download or read book INFORMS Analytics Body of Knowledge written by James J. Cochran and published by John Wiley & Sons. This book was released on 2018-10-23 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Standardizes the definition and framework of analytics #2 on Book Authority’s list of the Best New Analytics Books to Read in 2019 (January 2019) We all want to make a difference. We all want our work to enrich the world. As analytics professionals, we are fortunate - this is our time! We live in a world of pervasive data and ubiquitous, powerful computation. This convergence has inspired and accelerated the development of both analytic techniques and tools and this potential for analytics to have an impact has been a huge call to action for organizations, universities, and governments. This title from Institute for Operations Research and the Management Sciences (INFORMS) represents the perspectives of some of the most respected experts on analytics. Readers with various backgrounds in analytics – from novices to experienced professionals – will benefit from reading about and implementing the concepts and methods covered here. Peer reviewed chapters provide readers with in-depth insights and a better understanding of the dynamic field of analytics The INFORMS Analytics Body of Knowledge documents the core concepts and skills with which an analytics professional should be familiar; establishes a dynamic resource that will be used by practitioners to increase their understanding of analytics; and, presents instructors with a framework for developing academic courses and programs in analytics.

Download or read book Mobility Data written by Chiara Renso and published by Cambridge University Press. This book was released on 2013-10-14 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mobility of people and goods is essential in the global economy. The ability to track the routes and patterns associated with this mobility offers unprecedented opportunities for developing new, smarter applications in different domains. Much of the current research is devoted to developing concepts, models, and tools to comprehend mobility data and make it manageable for these applications. This book surveys the myriad facets of mobility data, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis, with a specific focus on monitoring people in motion (drivers, airplane passengers, crowds, and even animals in the wild). Written by a renowned group of worldwide experts, it presents a consistent framework that facilitates understanding of all these different facets, from basic definitions to state-of-the-art concepts and techniques, offering both researchers and professionals a thorough understanding of the applications and opportunities made possible by the development of mobility data.

Download or read book Financial Modeling in Excel For Dummies written by Danielle Stein Fairhurst and published by John Wiley & Sons. This book was released on 2017-04-24 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: Make informed business decisions with the beginner's guide to financial modeling using Microsoft Excel Financial Modeling in Excel For Dummies is your comprehensive guide to learning how to create informative, enlightening financial models today. Not a math whiz or an Excel power-user? No problem! All you need is a basic understanding of Excel to start building simple models with practical hands-on exercises and before you know it, you'll be modeling your way to optimized profits for your business in no time. Excel is powerful, user-friendly, and is most likely already installed on your computer—which is why it has so readily become the most popular financial modeling software. This book shows you how to harness Excel's capabilities to determine profitability, develop budgetary projections, model depreciation, project costs, value assets and more. You'll learn the fundamental best practices and know-how of financial modeling, and how to put them to work for your business and your clients. You'll learn the tools and techniques that bring insight out of the numbers, and make better business decisions based on quantitative evidence. You'll discover that financial modeling is an invaluable resource for your business, and you'll wonder why you've waited this long to learn how! Companies around the world use financial modeling for decision making, to steer strategy, and to develop solutions. This book walks you through the process with clear, expert guidance that assumes little prior knowledge. Learn the six crucial rules to follow when building a successful financial model Discover how to review and edit an inherited financial model and align it with your business and financial strategy Solve client problems, identify market projections, and develop business strategies based on scenario analysis Create valuable customized templates models that can become a source of competitive advantage From multinational corporations to the mom-and-pop corner store, there isn't a business around that wouldn't benefit from financial modeling. No need to buy expensive specialized software—the tools you need are right there in Excel. Financial Modeling in Excel For Dummies gets you up to speed quickly so you can start reaping the benefits today!

Download or read book The Basics of Financial Modeling written by Jack Avon and published by Apress. This book was released on 2014-11-21 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to create and understand financial models that assess the value of your company, the projects it undertakes, and its future earnings/profit projections. Follow this step-by-step guide organized in a quick-read format to build an accurate and effective financial model from the ground up. In this short book, The Basics of Financial Modeling—an abridgment of the Handbook of Financial Modeling—author Jack Avon equips business professionals who are familiar with financial statements and accounting reports to become truly proficient. Based on the author's extensive experience building models in business and finance, and teaching others to do the same, this book takes you through the financial modeling process, starting with a general overview of the history and evolution of financial modeling. It then moves on to more technical topics, such as the principles of financial modeling and the proper way to approach a financial modeling assignment, before covering key application areas for modeling in Microsoft Excel. What You'll Learn Understand the accounting and finance concepts that underpin working financial models Approach financial issues and solutions from a modeler's perspective Think about end users when developing a financial model Plan, design, and build a financial model Who This Book Is For Beginning to intermediate modelers who wish to expand and enhance their knowledge of using Excel to build and analyze financial models