Discover how visualization turns data into action Tableau gives you the power to understand your data and put it in a format that is appealing and meaningful for everyone who needs to see it. Tableau For Dummies walks you through the steps to turn your data into a story that inspires action. This easy-to-understand guide offers insights from an enterprise data pro on how to transform data into a clear and memorable visual presentation. Navigate the Tableau user interface and connect to data sources Use drag-and-drop features to create stunning visualizations Work with templates, add graphs, and create clear charts Export your visualizations to multiple formats for easy sharing This is the perfect Dummies software guide for business professionals who need to better derive value from that all-important data.

Turn your R code into packages that others can easily install and use. With this fully updated edition, developers and data scientists will learn how to bundle reusable R functions, sample data, and documentation together by applying the package development philosophy used by the team that maintains the "tidyverse" suite of packages. In the process, you'll learn how to automate common development tasks using a set of R packages, including devtools, usethis, testthat, and roxygen2. Authors Hadley Wickham and Jennifer Bryan from Posit (formerly known as RStudio) help you create packages quickly, then teach you how to get better over time. You'll be able to focus on what you want your package to do as you progressively develop greater mastery of the structure of a package. With this book, you will: Learn the key components of an R package, including code, documentation, and tests Streamline your development process with devtools and the RStudio IDE Get tips on effective habits such as organizing functions into files Get caught up on important new features in the devtools ecosystem Learn about the art and science of unit testing, using features in the third edition of testthat Turn your existing documentation into a beautiful and user friendly website with pkgdown Gain an appreciation of the benefits of modern code hosting platforms, such as GitHub

Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse—a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly. You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way. You'll understand how to: Visualize: Create plots for data exploration and communication of results Transform: Discover variable types and the tools to work with them Import: Get data into R and in a form convenient for analysis Program: Learn R tools for solving data problems with greater clarity and ease Communicate: Integrate prose, code, and results with Quarto

In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive sub-domains. To this end, the book will aim to review and highlight the challenges faced by Intelligent Analytics in Industry 4.0 and present the recent developments done to address those challenges.

Learn to use analytics more effectively, convert data into value and facilitate smarter and better decision-making for your organization.

Upgrade your career and organization with this handbook offering expert guidance on the business analysis role, supported by tools and templates.

Microsoft Power BI Machine Learning and OpenAI offers a comprehensive exploration into advanced data analytics and artificial intelligence using Microsoft Power BI. Through hands-on, workshop-style examples, readers will discover the integration of machine learning models and OpenAI features to enhance business intelligence. This book provides practical examples, real-world scenarios, and step-by-step guidance. What this Book will help me do Learn to apply machine learning capabilities within Power BI to create predictive analytics Understand how to integrate OpenAI services to build enhanced analytics workflows Gain hands-on experience in using R and Python for advanced data visualization in Power BI Master the skills needed to build and deploy SaaS auto ML models within Power BI Leverage Power BI's AI visuals and features to elevate data storytelling Author(s) Greg Beaumont, an expert in data science and business intelligence, brings years of experience in Power BI and analytics to this book. With a focus on practical applications, Greg empowers readers to harness the power of AI and machine learning to elevate their data solutions. As a consultant and trainer, he shares his deep knowledge to help readers unlock the full potential of their tools. Who is it for? This book is ideal for data analysts, BI professionals, and data scientists who aim to integrate machine learning and OpenAI into their workflows. If you're familiar with Power BI's fundamentals and are eager to explore its advanced capabilities, this guide is tailored for you. Perfect for professionals looking to elevate their analytics to a new level, combining data science concepts with Power BI's features.

Survey Development: A Theory-Driven Mixed Methods Approach provides both an overview of standard methods and tools for developing and validating surveys and a conceptual basis for survey development.

Whether you're a catalyst for organizational change or have the support you need to create an engineering culture that embraces A/B testing, this book will help you do it right. The step-by-step instructions will demystify the entire process, from constructing an A/B test to breaking down the decision factors to build an engineering platform. When you're ready to run the A/B test of your dreams, you'll have the perfect blueprint. With smart, tactful approaches to orchestrating A/B testing on a product, you'll quickly discover how to reap all the benefits that A/B testing has to offer - benefits that span your users, your product, and your team. Take the reins today, and be the change you want to see in your engineering and product organizations. Develop a hypothesis statement that's backed with metrics that demonstrate if your prediction for the experiment is correct. Build more inclusive products by leveraging audience segmentation strategies and ad-hoc post analysis to better understand the impact of changes on specific user groups. Determine which path is best for your team when deciding whether to go with a third-party A/B test framework or to build the A/B testing platform in-house. And finally, learn how to cultivate an experimentation-friendly culture within your team. Leverage the A/B testing methodology to demonstrate the impact of changes on a product to your users, your key business metrics, and the way your team works together. After all, if you aren't measuring the impact of the changes you make, how will you know if you're truly making improvements?

Over the past 10 years, data analytics and data visualization have become essential components of an enterprise information strategy. And yet, the adoption of data analytics has remained remarkably static, reaching no more than 30% of potential users. This book explores the most important techniques for taking that adoption further: embedding analytics into the workflow of our everyday operations. Authors Donald Farmer and Jim Horbury show business users how to improve decision making without becoming analytics specialists. You'll explore different techniques for exchanging data, insights, and events between analytics platforms and hosting applications. You'll also examine issues including data governance and regulatory compliance and learn best practices for deploying and managing embedded analytics at scale. Learn how data analytics improves business decision making and performance Explore advantages and disadvantages of different embedded analytics platforms Develop a strategy for embedded analytics in an organization or product Define the architecture of an embedded solution Select vendors, platforms, and tools to implement your architecture Hire or train developers and architects to build the embedded solutions you need Understand how embedded analytics interacts with traditional analytics

This textbook surveys new and emergent methods for doing research in critical security studies, filling a gap in the literature. The 2nd edition has been revised and updated.

Visualize Complex Processes with Microsoft Visio is your go-to guide for learning how to effectively create and use process flow diagrams. By using Visio's built-in templates and features, this book enables you to document business processes and workflows clearly and professionally, ensuring better understanding and communication. What this Book will help me do Understand how to select and use flowchart types for visually communicating processes. Learn to navigate Visio's interface and features to efficiently create diagrams. Master integrating process flows with data and other M365 apps for added insights. Discover how to securely store and share diagrams for collaboration. Gain skills to customize templates and create diagrams that meet professional standards. Author(s) David Parker and Senaj Lelic are seasoned experts in business process visualization and Microsoft Visio. They bring years of experience in designing complex workflows and teaching professionals how to use Visio effectively. Their approachable writing style ensures clear guidance, empowering readers to achieve practical outcomes. Who is it for? This book is tailored for managers, analysts, and designers seeking to improve their skills in process visualization. Beginner Visio users will find step-by-step instructions valuable, while advanced users can explore tips for customization and integration. If you aim to enhance clarity in communications through professional diagrams, this book is for you.

A comprehensive and fully visual guide to Microsoft Power BI Teach Yourself VISUALLY Power BI collects all the resources you need to master the everyday use of Microsoft's powerful data visualization software and delivers them in a single, easy-to-use volume. Fully illustrated, step-by-step instructions are combined with crystal-clear screenshots that walk you through the basic and advanced functions of Microsoft Power BI. Teach Yourself VISUALLY Power BI offers the best visual learning techniques with complete source material about the interface and substance of Power BI, as well as: Stepwise guidance on working with, transforming, and processing data sources Instructions for customizing data visualizations to create informative and presentation-ready charts and graphs Full-color, two-page tutorials on the more advanced features of Power BI, including app integrations and data access with DAX The fastest, easiest way for visual learners to get a handle on Microsoft Power BI, Teach Yourself VISUALLY Power BI is a can't-miss resource, loaded with useful tips for newbies and experts alike.

Welcome to this step-by-step guide for Excel users, data analysts, and finance specialists. It is designed to take you through practical report and development scenarios, including both the approach and the technical challenges. This book will equip you with an understanding of the overall Power Platform use case for addressing common business challenges. While Power BI continues to be an excellent tool of choice in the BI space, Power Platform is the real game changer. Using an integrated architecture, a small team of citizen developers can build solutions for all kinds of business problems. For small businesses, Power Platform can be used to build bespoke CRM, Finance, and Warehouse management tools. For large businesses, it can be used to build an integration point for existing systems to simplify reporting, operation, and approval processes. The author has drawn on his15 years of hands-on analytics experience to help you pivot from the traditional Excel-based reporting environment. By using different business scenarios, this book provides you with clear reasons why a skill is important before you start to dive into the scenarios. You will use a fast prototyping approach to continue to build exciting reporting, automation, and application solutions and improve them while you acquire new skill sets. The book helps you get started quickly with Power BI. It covers data visualization, collaboration, and governance practices. You will learn about the most practical SQL challenges. And you will learn how to build applications in PowerApps and Power Automate. The book ends with an integrated solution framework that can be adapted to solve a wide range of complex business problems. What You Will Learn Develop reporting solutions and business applications Understand the Power Platform licensing and development environment Apply Data ETL and modeling in Power BI Use Data Storytelling and dashboard design to better visualize data Carry out data operations with SQL and SharePoint lists Develop useful applications using Power Apps Develop automated workflows using Power Automate Integrate solutions with Power BI, Power Apps, and Power Automate to build enterprise solutions Who This Book Is For Next-generation data specialists, including Excel-based users who want to learn Power BI and build internal apps; finance specialists who want to take a different approach to traditional accounting reports; and anyone who wants to enhance their skill set for the future job market.

Prepare for Microsoft Exam PL-900. Demonstrate your real-world knowledge of the fundamentals of Microsoft Power Platform, including its business value, core components, and the capabilities and advantages of Power BI, Power Apps, Power Automate, and Power Virtual Agents. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Power Platform Fundamentals level. Focus on the expertise measured by these objectives: Describe the business value of Power Platform Identify the Core Components of Power Platform Demonstrate the capabilities of Power BI Demonstrate the capabilities of Power Apps Demonstrate the capabilities of Power Automate Demonstrate the capabilities of Power Virtual Agents This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are a business user, functional consultant, or other professional who wants to improve productivity by automating business processes, analyzing data, creating simple app experiences, or developing business enhancements to Microsoft cloud solutions. About the Exam Exam PL-900 focuses on knowledge needed to describe the value of Power Platform services and of extending solutions; describe Power Platform administration and security; describe Common Data Service, Connectors, and AI Builder; identify common Power BI components; connect to and consume data; build basic dashboards with Power BI; identify common Power Apps components; build basic canvas and model-driven apps; describe Power Apps portals; identify common Power Automate components; build basic flows; describe Power Virtual Agents capabilities; and build and publish basic chatbots. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Power Platform Fundamentals certification, demonstrating your understanding of Power Platforms core capabilitiesfrom business value and core product capabilities to building simple apps, connecting data sources, automating basic business processes, creating dashboards, and creating chatbots. With this certification, you can move on to earn specialist certifications covering more advanced aspects of Power Apps and Power BI, including Microsoft Certified: Power Platform App Maker Associate and Power Platform Data Analyst Associate. See full details at: microsoft.com/learn

Expert Data Modeling with Power BI, Second Edition, serves as your comprehensive guide to mastering data modeling using Power BI. With clear explanations, actionable examples, and a focus on hands-on learning, this book takes you through the concepts and advanced techniques that will enable you to build high-performing data models tailored to real-world requirements. What this Book will help me do Master time intelligence and virtual tables in DAX to enhance your data models. Understand best practices for creating efficient Star Schemas and preparing data in Power Query. Deploy advanced modeling techniques such as calculation groups, aggregations, and incremental refresh. Manage complex data models and streamline them to improve performance. Leverage data marts and data flows within Power BI for modularity and scalability. Author(s) Soheil Bakhshi is a seasoned expert in data visualization and analytics with extensive experience in leveraging Power BI for business intelligence solutions. Passionate about educating others, he combines practical insights and technical knowledge to make learning accessible and effective. His approachable writing style reflects his commitment to helping readers succeed. Who is it for? This book is ideal for business intelligence professionals, data analysts, or report developers with basic knowledge of Power BI and experience with Star Schema concepts. Whether you're looking to refine your data modeling skills or expand your expertise in advanced features, this guide aims to help you achieve your goals efficiently.

Advance your skills in building predictive models with SAS! Building Regression Models with SAS: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models: general linear models quantile regression models logistic regression models generalized linear models generalized additive models proportional hazards regression models tree models models based on multivariate adaptive regression splines Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.

TWO-DIMENSIONAL (2D) NMR METHODS Practical guide explaining the fundamentals of 2D-NMR for experienced scientists as well as relevant for advanced students Two-Dimensional (2D) NMR Methods is a focused work presenting an overview of 2D-NMR concepts and techniques, including basic principles, practical applications, and how NMR pulse sequences work. Contributed to by global experts with extensive experience in the field, Two-Dimensional (2D) NMR Methods provides in-depth coverage of sample topics such as: Basics of 2D-NMR, data processing methods (Fourier and beyond), product operator formalism, basics of spin relaxation, and coherence transfer pathways Multidimensional methods (single- and multiple-quantum spectroscopy), NOESY (principles and applications), and DOSY methods Multiple acquisition strategies, anisotropic NMR in molecular analysis, ultrafast 2D methods, and multidimensional methods in bio-NMR TROSY (principles and applications), field-cycling and 2D NMR, multidimensional methods and paramagnetic NMR, and relaxation dispersion experiments This text is a highly useful resource for NMR specialists and advanced students studying NMR, along with users in research, academic and commercial laboratories that study or conduct experiments in NMR.

All About Bioinformatics: From Beginner to Expert provides readers with an overview of the fundamentals and advances in the _x001F_field of bioinformatics, as well as some future directions. Each chapter is didactically organized and includes introduction, applications, tools, and future directions to cover the topics thoroughly. The book covers both traditional topics such as biological databases, algorithms, genetic variations, static methods, and structural bioinformatics, as well as contemporary advanced topics such as high-throughput technologies, drug informatics, system and network biology, and machine learning. It is a valuable resource for researchers and graduate students who are interested to learn more about bioinformatics to apply in their research work. Presents a holistic learning experience, beginning with an introduction to bioinformatics to recent advancements in the field Discusses bioinformatics as a practice rather than in theory focusing on more application-oriented topics as high-throughput technologies, system and network biology, and workflow management systems Encompasses chapters on statistics and machine learning to assist readers in deciphering trends and patterns in biological data

This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden patterns and relationships, predict future outcomes, optimize efficiency and improve the performance of organizations. You’ll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. Practical Business Analytics Using R and Python also features new chapters covering databases, SQL, Neural networks, Text Analytics, and Natural Language Processing.Part one begins with an introduction to analytics, the foundations required to perform data analytics, and explains different analytics terms and concepts such as databases and SQL, basic statistics, probability theory, and data exploration. Part two introduces predictive models using statistical machine learning and discusses concepts like regression, classification, and neural networks. Part three covers two of the most popular unsupervised learning techniques, clustering and association mining, as well as text mining and natural language processing (NLP). The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy. Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics. What You Will Learn Master the mathematical foundations required for business analytics Understand various analytics models and data mining techniques such as regression, supervised machine learning algorithms for modeling, unsupervised modeling techniques, and how to choose the correct algorithm for analysis in any given task Use R and Python to develop descriptive models, predictive models, and optimize models Interpret and recommend actions based on analytical model outcomes Who This Book Is For Software professionals and developers, managers, and executives who want to understand and learn the fundamentals of analytics using R and Python.

An Introduction to Economic Dynamics provides a framework for students to appreciate and understand the basic intuition behind economic models and to experiment with those models using simulation techniques in MATLAB.

This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems.

Discover how to effectively forecast time series data using Prophet, the versatile open-source tool developed by Meta. Whether you're a business analyst or a machine learning expert, this book provides comprehensive insights into creating, diagnosing, and refining forecasting models. By mastering Prophet, you'll be equipped to make accurate predictions that drive decisions. What this Book will help me do Master the core principles of using Prophet for time series forecasting. Ensure your forecasts are accurate and robust for better decision-making. Gain experience in handling real-world forecasting challenges, like seasonality and outliers. Learn how to fine-tune and optimize models using additional regressors. Understand productionalization of forecasting models to apply solutions at scale. Author(s) Greg Rafferty is a seasoned data scientist specializing in time series analysis and machine learning. With years of practical experience building forecasting models in industries ranging from finance to e-commerce, Greg is dedicated to teaching accessible and actionable approaches to data science. Through clear explanations and practical examples, he empowers readers to solve challenging forecasting problems with confidence. Who is it for? Ideal for data scientists, business analysts, machine learning engineers, and software developers seeking to enhance their forecasting skills with Prophet. Whether you're familiar with time series concepts or just starting to explore forecasting methods, this book helps you advance from fundamental understanding to practical application of state-of-the-art techniques for impactful results.

BIOINFORMATICS TOOLS FOR Pharmaceutical DRUG PRODUCT DLEVELOPMENT A timely book that details bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies, for drug development in the pharmaceutical and medical sciences industries. The book contains 17 chapters categorized into 3 sections. The first section presents the latest information on bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies. The following 2 sections include bioinformatics tools for the pharmaceutical sector and the healthcare sector. Bioinformatics brings a new era in research to accelerate drug target and vaccine design development, improving validation approaches as well as facilitating and identifying side effects and predicting drug resistance. As such, this will aid in more successful drug candidates from discovery to clinical trials to the market, and most importantly make it a more cost-effective process overall. Readers will find in this book: Applications of bioinformatics tools for pharmaceutical drug product development like process development, pre-clinical development, clinical development, commercialization of the product, etc.; The ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach; The broad and deep background, as well as updates, on recent advances in both medicine and AI/ML that enable the application of these cutting-edge bioinformatics tools. Audience The book will be used by researchers and scientists in academia and industry including drug developers, computational biochemists, bioinformaticians, immunologists, pharmaceutical and medical sciences, as well as those in artificial intelligence and machine learning.

This volume deals with two complementary topics. On one hand the book deals with the problem of determining the the probability distribution of a positive compound random variable, a problem which appears in the banking and insurance industries, in many areas of operational research and in reliability problems in the engineering sciences. On the other hand, the methodology proposed to solve such problems, which is based on an application of the maximum entropy method to invert the Laplace transform of the distributions, can be applied to many other problems. The book contains applications to a large variety of problems, including the problem of dependence of the sample data used to estimate empirically the Laplace transform of the random variable. Contents Introduction Frequency models Individual severity models Some detailed examples Some traditional approaches to the aggregation problem Laplace transforms and fractional moment problems The standard maximum entropy method Extensions of the method of maximum entropy Superresolution in maxentropic Laplace transform inversion Sample data dependence Disentangling frequencies and decompounding losses Computations using the maxentropic density Review of statistical procedures