| Book | Brief | |
|---|---|---|
| The real tragedy of a company failing while using analytics is the fact that its leaders will have the data to explain the failure, but they won't have the capabilities in place to filter the data and convert it into actionable business insights. One implication of Big Data is that we need to adapt . . . quickly. A Practitioner's Guide to Business Analytics integrates powerful strategies for leveraging analytics inside a business with a how-to playbook of tactics to make it happen. The case for competing based on analytics is clear, but until now, there hasn't been authoritative guidance for inciting a corporate community to evolve into a thriving, analytics-driven environment. This hands-on book gives you the tools, knowledge, and strategies to capture the level of organizational commitment you need to get business analytics up and running in your company. It helps you define what business analytics is, quantify the exponential value it brings to an organization, and show others how to harness its power to gain advantage over competitors. |
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Saturday, July 25, 2020
A PRACTITIONER'S GUIDE TO BUSINESS ANALYTICS
AWS Certified Data Analytics Study Guide:
| Book | Brief | |
|---|---|---|
| This AWS Specialty Exam guide gets you ready for certification testing with expert content, real-world knowledge, key exam concepts, and topic reviews. Gain confidence by studying the subject areas and working through the practice questions. Big data concepts covered in the guide include:
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Global Entrepreneurship Analytics: Using GEM Data
| Book | Brief | |
|---|---|---|
| This innovative book proposes new methodologies for the measurement of entrepreneurship by applying techniques of demography, engineering, mathematics and statistics.
Using the data from the Global Entrepreneurship Monitor (GEM), statistical demographic techniques are used for the evaluation of data quality (EDQ), and a new methodology for the estimation of Specific Entrepreneurship Rates (SER) and the Global Entrepreneurship Rate (GER) is proposed. At the same time the authors present artificial intelligence techniques such as Fuzzy Time Series (FTS) to forecast data series of the entrepreneurial population. |
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Business Intelligence, Analytics, and Data Science: A Managerial Perspective
| Book | Brief | |
|---|---|---|
| For courses on Business Intelligence or Decision Support Systems.
A managerial approach to understanding business intelligence systems. To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice. |
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Fundamentals of HR Analytics:
| Book | Brief | |
|---|---|---|
| The future of the Human Resource Management profession is inextricably linked to understanding data analytics. Building on traditional HR skillsets, the book makes understanding and engaging with data analytics possible for professionals at all levels. Leveraging key statistical and financial concepts, including ROI and people productivity, and commonly available tools such as Workday and Tableau, the authors explore key skills and tasks in an accessible and illuminating way, including:
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Clinical Analytics and Data Management for the DNP
| Book | Brief | |
|---|---|---|
| This is the only text to deliver the strong data management knowledge and skills that are required competencies for all DNP students. It enables readers to design data tracking and clinical analytics in order to rigorously evaluate clinical innovations and programs for improving clinical outcomes and to document and analyze change. The text takes the DNP student step by step through the complete process of data management from planning through presentation, and encompasses the scope of skills required for students to apply relevant analytics to systematically and confidently tackle the clinical interventions data obtained as part of the DNP student project. Of particular value is a progressive case study illustrating multiple techniques and methods throughout the chapters. Sample data sets and exercises, along with objectives, references, and examples in each chapter, reinforce information. |
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Big Data Science & Analytics: A Hands-On Approach
| Book | Brief | |
|---|---|---|
| We are living in the dawn of what has been termed as the "Fourth Industrial Revolution"? Data and information are fuel of this new age where powerful analytics algorithms burn this fuel to generate decisions that are expected to create a smarter and more efficient world for all of us to live in. This book deals with collection, storage, processing and analysis of massive-scale data. Industry surveys, by Gartner and e-Skills, for instance, predict that there will be over 2 million job openings for engineers and scientists trained in the area of data science and analytics alone, and that the job market is in this area is growing at a 150 percent year-over-year growth rate. |
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Analytics Best Practices: A Business-driven Playbook?
| Book | Brief | |
|---|---|---|
| This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are:
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Business Analytics: Data Analysis & Decision Making
| Book | Brief | |
|---|---|---|
| Become a master of data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 6E! This popular quantitative methods text helps you maximize your success with its proven teach-by-example approach, student-friendly writing style, and complete Excel 2016 integration. (It is also compatible with Excel 2013, 2010, and 2007.) The text devotes three online chapters to advanced statistical analysis. Chapters on data mining and importing data into Excel emphasize tools commonly used under the Business Analytics umbrella -- including Microsoft Excel's ,Power BI's suite. Up-to-date problem sets and cases demonstrate how chapter concepts relate to real-world practice. In addition, the Companion Website includes data and solutions files, PowerPoint slides, SolverTable for sensitivity analysis, and the Palisade DecisionTools Suite (@RISK, BigPicture, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver). |
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Advances in Analytics for Learning and Teaching
| Book | Brief | |
|---|---|---|
| This book includes a collection of expanded papers from the 2019 Sino-German Symposium on AI-supported educational technologies, which was held in Wuhan, China, March, 2019. The contributors are distinguished researchers from computer science and learning science.
The contributions are organized in four sections: (1) Overviews and systematic perspectives , (2) Example Systems, (3) Algorithms, and (4) Insights gained from empirical studies. For example, different data mining and machine learning methods to quantify different profiles of a learner in different learning situations (including interaction patterns, cognitive modes, knowledge skills, interests and emotions etc.) as well as connections to measurements in psychology and learning sciences are discussed in the chapters. |
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Sunday, July 19, 2020
Digital Marketing Analytics: Making Sense of Consumer Data?
| Book | Brief | |
|---|---|---|
| Why hasn’t all that data delivered a whopping competitive advantage? Because you’ve barely begun to use it, that’s why! Need help chopping the problem down to size, solve every piece of the puzzle, and integrate a virtually frictionless system for moving from data to decision, action to results? This will help with the following;
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R for Everyone: Advanced Analytics and Graphics?
| Book | Brief | |
|---|---|---|
| Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. A perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. |
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Analytic Geometry (Calculus with Trigonometry)?
| Book | Brief | |
|---|---|---|
| Aimed at first and second year undergraduate students in mathematics, the physical sciences, and engineering, and written by two authorities in the field, this book will be required reading for courses that follow a 'problem-solving' approach to teaching calculus. The main philosophy of calculus is presented through many examples and applications to explain its abstract notions and concepts. A solutions manual demonstrating the workings of each example accompanies the book. |
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Administration of Symantec Security Analytics 8.0
| Book | Brief | |
|---|---|---|
| E |  You can feel confident that using our practice test questions and answers, you will be fully prepared to pass the CompTIA exams. CompTIA Tests Training Material Includes: Administration of Symantec Security Analytics |
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Big Data: How Data Analytics Is Transforming the World
| Book | Brief | |
|---|---|---|
| In our age of accelerating progress in so many fields, it’s easy to lose sight of the underlying innovation that makes the data analytics revolution possible. These 24 lectures introduce you to the key concepts, methods, and accomplishments of this versatile approach to problem solving. You need no expertise in mathematics to follow this exciting story. Tim Chartier, professor of mathematics and computer science, explains the basic computational techniques used in data analytics, but his focus is on how these ideas are applied and the amazing results they achieve. His case histories make these lectures both accessible and entertaining. He takes you behind the scenes to witness many examples of data analysis in action, including the pitfalls and potential of Internet traffic analysis, algorithms that aim to predict what customers want, some of the best defenses for keeping your personal data private, how methods for filling out March Madness game brackets can be applied to other problems, and much more. Professor Chartier is a champion of the fun, challenge, and breathtaking power of mathematics - qualities that are beautifully illustrated in data analytics. And with his enjoyable lectures, you’ll discover concepts and tools that are transforming the world - and that you can use to transform your own life. It’s like watching a thrilling spectator sport that invites you to suit up and join the action! |
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Genogram Analytics?
| Book | Brief | |
|---|---|---|
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Marketing Strategy...Based on First Principles and Data Analytics?
| Book | Brief | |
|---|---|---|
| 1. All customers differ 2. All customers change 3. All competitors react 4. All resources are limited Structured around these four First Principles of Marketing, this important new textbook offers a unique and extensively classroom-tested approach to marketing strategy. It provides a structured framework to develop effective strategies to deal with diverse marketing problems while integrating data analytics into the decision-making process. Authored by world-leading experts in marketing strategy, Marketing Strategy: First Principles and Data Analytics is the ideal companion for undergraduate, MBA and Executive MBA students of marketing, and practicing executives looking to bring a more systematic approach to their firms’ marketing strategy efforts. |
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Clinical Analytics and Data Management for the DNP?
| Book | Brief | |
|---|---|---|
| This is the only text to deliver the strong data management knowledge and skills that are required competencies for all DNP students. It enables readers to design data tracking and clinical analytics in order to rigorously evaluate clinical innovations and programs for improving clinical outcomes and to document and analyze change. This second edition has been expanded and updated to address major changes in our healthcare environment. Incorporating faculty and student input, it now includes modalities such as SPSS, Excel, and Tableau to address diverse data management tasks. Eleven new chapters cover the use of big data analytics, ongoing progress toward value-based payment, the Affordable Care Act and its future, shifting of risk and accountability to hospitals and clinicians, advancement of nursing quality indicators, and new requirements for Magnet® certification. The text takes the DNP student step by step through the complete process of data management from planning through presentation, and encompasses the scope of skills required for students to apply relevant analytics to systematically and confidently tackle the clinical interventions data obtained as part of the DNP student project. Of particular value is a progressive case study illustrating multiple techniques and methods throughout the chapters. Sample data sets and exercises, along with objectives, references, and examples in each chapter, reinforce information. |
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Forensic Analytics: Methods and Techniques?
| Book | Brief | |
|---|---|---|
| Each chapter, where applicable, includes one or more cases showing how the tests under discussion could have detected the fraud or anomalies. Also includes two chapters each describing multi-million-dollar fraud schemes and the insights that can be learned from those examples. These interesting real-world examples help to make the text accessible and understandable for accounting professionals and accounting students without rigorous backgrounds in mathematics and statistics. Emphasizing practical applications, the new edition shows how to use either Excel or Access to run these analytics tests. This authoritative book:
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Analytic Methods in Sports?
| Book | Brief | |
|---|---|---|
| One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter. |
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Predictive HR Analytics, Text Mining & Network Analysis with Excel?
| Book | Brief | |
|---|---|---|
| Predictive HR Analytics, Text Mining & Organizational Network Analysis (ONA) are hot topics and powerful techniques to improve organization effectiveness. Best Buy is able to predict that a 0.1% increase in employee engagement results in an increase of $100,000 in the store’s annual income! VoloMetrix found that a salesperson’s network size within their company is a more important leading indicator of sales, than the time salespeople spend with customers! You don't need to spend months learning R programming & you don't need to buy expensive SPSS statistical software. This is the only book that teaches you how to use Microsoft Excel for Predictive HR Analytics, Text Mining & Organizational Network Analysis (ONA) with step-by-step print-screen instructions: |
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