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  • 1
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Tableau (Computer file) ; Information visualization ; Visual analytics ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Illustrate your data in a more interactive way by implementing data visualization principles and creating visual stories using Tableau About This Book Use data visualization principles to help you to design dashboards that enlighten and support business decisions Integrate your data to provide mashed-up dashboards Connect to various data sources and understand what data is appropriate for Tableau Public Understand chart types and when to use specific chart types with different types of data Who This Book Is For Data scientists who have just started using Tableau and want to build on the skills using practical examples. Familiarity with previous versions of Tableau will be helpful, but not necessary. What You Will Learn Customize your designs to meet the needs of your business using Tableau Use Tableau to prototype, develop, and deploy the final dashboard Create filled maps and use any shape file Discover features of Tableau Public, from basic to advanced Build geographic maps to bring context to data Create filters and actions to allow greater interactivity to Tableau Public visualizations and dashboards Publish and embed Tableau visualizations and dashboards in articles In Detail With increasing interest for data visualization in the media, businesses are looking to create effective dashboards that engage as well as communicate the truth of data. Tableau makes data accessible to everyone, and is a great way of sharing enterprise dashboards across the business. Tableau is a revolutionary toolkit that lets you simply and effectively create high-quality data visualizations. This course starts with making you familiar with its features and enable you to develop and enhance your dashboard skills, starting with an overview of what dashboard is, followed by how you can collect data using various mathematical formulas. Next, you'll learn to filter and group data, as well as how to use various functions to present the data in an appealing and accurate way. In the first module, you will learn how to use the key advanced string functions to play with data and images. You will be walked through the various features of Tableau including dual axes, scatterplot matrices, heat maps, and sizing.In the second module, you'll start with getting your data into Tableau, move onto generating progressively complex graphics, and end with the finishing touches and packaging your work for distribution. This module is filled with practical examples to help you create fi...
    Note: Authors: Jen Stirrup, Ashutosh Nandeshwar, Ashley Ohmann, Matt Floyd. Cf. Credits page. - Includes bibliographical references and index. - Description based on online resource; title from title page (Safari, viewed October 6, 2016)
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  • 2
    Language: English
    Pages: 1 online resource (1 streaming video file (1 hr., 47 min., 28 sec.)) , digital, sound, color
    Keywords: Artificial intelligence ; Machine learning ; Information visualization ; Electronic videos ; local
    Abstract: "Deep learning (DL) is an exciting new data technology that's creating business value for companies like Google, Yahoo, Microsoft, Amazon, Netflix, Spotify, and more. This course explains DL's core concepts, demystifies the math and science underlying the technology, and reviews its strengths, weaknesses, challenges, and risks from a strategic perspective. Business executives seeking a market-focused introduction to this technology will come away with the ability to articulate DL's core concepts and an understanding of how they fit together to produce business value."--Resource description page.
    Note: Title from title screen (viewed August 23, 2017). - Date of publication from resource description page
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  • 3
    ISBN: 9781786460240 , 1786460246
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Data mining ; Data processing ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of R About This Book A comprehensive guide that will bring out the creativity in you to visualize the results of complex calculations using Tableau and R Combine Tableau analytics and visualization with the power of R using this step-by-step guide Wondering how R can be used with Tableau? This book is your one-stop solution. Who This Book Is For This book will appeal to Tableau users who want to go beyond the Tableau interface and deploy the full potential of Tableau, by using R to perform advanced analytics with Tableau. A basic familiarity with R is useful but not compulsory, as the book will start off with concrete examples of R and will move quickly into more advanced spheres of analytics using online data sources to support hands-on learning. Those R developers who want to integrate R in Tableau will also benefit from this book. What You Will Learn Integrate Tableau's analytics with the industry-standard, statistical prowess of R. Make R function calls in Tableau, and visualize R functions with Tableau using RServe. Use the CRISP-DM methodology to create a roadmap for analytics investigations. Implement various supervised and unsupervised learning algorithms in R to return values to Tableau. Make quick, cogent, and data-driven decisions for your business using advanced analytical techniques such as forecasting, predictions, association rules, clustering, classification, and other advanced Tableau/R calculated field functions. In Detail Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics. By the end of this book, you will get to grips with advan...
    Note: Includes bibliographical references and index. - Description based on online resource; title from cover (Safari, viewed September 12, 2017)
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