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Advanced Business Analytics by The present book provides an enterprise-wide guide for anyone interested in pursuing analytic methods in order to compete effectively. It supplements more general texts on statistics and data mining by providing an introduction from leading practitioners in business analytics and real case studies of firms using advanced analytics to gain a competitive advantage in the marketplace. In the era of "big data" and competing analytics, this book provides practitioners applying business analytics with an overview of the quantitative strategies and techniques used to embed analysis results and advanced algorithms into business processes and create automated insight-driven decisions within the firm. Numerous studies have shown that firms that invest in analytics are more likely to win in the marketplace. Moreover, the Internet of Everything (IoT) for manufacturing and social-local-mobile (SOLOMO) for services have made the use of advanced business analytics even more important for firms. These case studies were all developed by real business analysts, who were assigned the task of solving a business problem using advanced analytics in a way that competitors were not. Readers learn how to develop business algorithms on a practical level, how to embed these within the company and how to take these all the way to implementation and validation.
Big Data Demystified by Big Data is a big topic, based on simple principles. Guided by leading expert in the field, David Stephenson, you will be amazed at how you can transform your company, and significantly improve KPIs across a broad range of business units and applications. Find out how an ecommerce company avoided two million product returns per year, how a newspaper saw triple-digit annual growth in digital subscriptions, how researchers in England learned to better detect pending cardiovascular problems, and how AI programs taught themselves to win games using techniques that even their human programmers didn't understand, all thanks to big data. Find out also how one company realized it could swap a million dollar hardware system with a twenty thousand dollar replacement. With simple and straightforward chapters that allow you to map examples onto your own business, Big Data Demystified will help you: · Know which data is most useful to collect now and why it's important to start collecting that data as soon as possible. · Understand big data and data science and how they can help you reach your business goals and gain competitive advantage. · Use big data to understand where you are now and how you can improve in the future. · Understand factors in choosing a big data system, including whether to go with cloud-based solutions. · Construct your big data team in a way that supports an effective strategy and helps make your business more data-driven. BIG DATA MAKES A BIG DIFFERENCE "Read this book! It is an essential guide to using data in a practical way that drives results." Ian McHenry, CEO Beyond Pricing "This is the book we've been missing: big data explained without the complexity." Marc Salomon, Professor in Decision Sciences and Dean at University of Amsterdam Business School "Big Data for the rest of us! I have never come across a book that is so full of practical advice, actionable examples and helpful explanations. Read this one book and start executing Big Data at your workplace tomorrow!" Tobias Wann CEO at @Leisure Group
The Big Picture: How to Use Data Visualization to Make Better Decisions--Faster by Not a data expert? Here's an engaging and entertaining guide to interpreting and drawing insights from any chart, graph, or other data visualization you'll encounter. You're a business professional, not a data scientist. How do you make heads or tails of the data visualizations that come across your desk--let alone make critical business decisions based on the information they're designed to convey? In The Big Picture, top data visualization consultant Steve Wexler provides the tools for developing the graphical literacy you need to understand the data visualizations that are flooding your inbox--and put that data to use. Packed with the best four-color examples created in Excel, Tableau, Power BI, and Qlik, among others, this one-stop resource empowers you to extract the most important information from data visualizations quickly and accurately, act on key insights, solve problems, and make the right decisions for your organization every time. 
Harnessing the Power of Analytics by This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they can be applied and explained within improving decisions.
HBR Guide to Data Analytics Basics for Managers (HBR Guide Series) by Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes
Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences by Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data's contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: * The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis * A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data * Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends * Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems * A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human-information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.
Introduction to R for Business Intelligence by Learn how to leverage the power of R for Business IntelligenceAbout This Book- Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful.- This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R.- Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide.Who This Book Is ForThis book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected.What You Will Learn- Extract, clean, and transform data- Validate the quality of the data and variables in datasets- Learn exploratory data analysis- Build regression models- Implement popular data-mining algorithms- Visualize results using popular graphs- Publish the results as a dashboard through Interactive Web Application frameworksIn DetailExplore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance.In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards.After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence.Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions-and all of this with the help of real-life examples.
Marketing Analytics by The authors of the pioneering Cutting-Edge Marketing Analytics return to the vital conversation of leveraging big data with Marketing Analytics: Essential Tools for Data-Driven Decisions, which updates and expands on the earlier book as we enter the 2020s. As they illustrate, big data analytics is the engine that drives marketing, providing a forward-looking, predictive perspective for marketing decision-making. The book presents actual cases and data, giving readers invaluable real-world instruction. The cases show how to identify relevant data, choose the best analytics technique, and investigate the link between marketing plans and customer behavior. These actual scenarios shed light on the most pressing marketing questions, such as setting the optimal price for one's product or designing effective digital marketing campaigns. Big data is currently the most powerful resource to the marketing professional, and this book illustrates how to fully harness that power to effectively maximize marketing efforts.
Profit Driven Business Analytics by Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the author team draws upon their recent research to share deep insight about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this guide provides invaluable guidance for practitioners seeking to reap the advantages of true business analytics. Despite widespread discussion surrounding the value of data in decision making, few businesses have adopted advanced analytic techniques in any meaningful way. This book shows you how to delve deeper into the data and discover what it can do for your business. Reinforce basic analytics to maximize profits Adopt the tools and techniques of successful integration Implement more advanced analytics with a value-centric approach Fine-tune analytical information to optimize business decisions Both data stored and streamed has been increasing at an exponential rate, and failing to use it to the fullest advantage equates to leaving money on the table. From bolstering current efforts to implementing a full-scale analytics initiative, the vast majority of businesses will see greater profit by applying advanced methods. Profit-Driven Business Analytics provides a practical guidebook and reference for adopting real business analytics techniques.
Social Media Data Mining and Analytics by Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.
Strategy Is Digital by This book presentsstrategies and practices to allow everyday companies to cope with thefundamentally changing landscape of business models and to take advantage ofthe huge business opportunities arising from the advent of big data. Itdevelops several case studies from companies in traditional industries likeLEGO, Yamato and Mediq, but also examines small start-ups like Space Tango,which is partnering with major multinationals to develop new business modelsusing big data. The book argues that businesses need to adapt and embark ontheir big data journey, helps them take the first step, and guides them alongtheir way. It presents successful examples and deducts essential takeawaylessons from them, equipping executives to capitalize on big data and enablingthem to make intelligent decisions in the big data transformation, giving theircompanies an essential competitive edge.