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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 boo...
Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of RAbout This Book* Comprehensive guide that will bring out the creativity inside you in visualizing 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 ForThis 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 ...
Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization. Springboarding from the skills that you already possess, this book adds AI to your organization's technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you'll learn how to choose the right model for your AI work and identify its value and validity. Use Power BI to build a good data model for AI Demystify the AI terminology that you need to know Identify AI project roles, responsibilities, and teams for AI Use AI models, including supervised machine learning techniques Develop and train models in Azure ML for consumption in Power BI Improve your business AI maturity level with Power BI Use the AI feedback loop to help you get started with the next project
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 ne...
Perform advanced dashboard, visualization, and analytical techniques with Tableau Desktop, Tableau Prep, and Tableau Server Key FeaturesUnique problem-solution approach to aid effective business decision-makingCreate interactive dashboards and implement powerful business intelligence solutionsIncludes best practices on using Tableau with modern cloud analytics servicesBook Description Tableau has been one of the most popular business intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. Tableau 2019.x Cookbook is full of useful recipes from industry experts, who will help you master Tableau skills and learn each aspect of Tableau's ec...
Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you’ll learn how to apply automated machine learning (AutoML), a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology. Building machine-learning models is an iterative and time-consuming process. Even those who know how to create ML models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply AutoML to your data right away. Learn how companies in different industries are benefiting from AutoML Get started with AutoML using Azure Explore aspects such as algorithm selection, auto featurization, and hyperparameter tuning Understand how data analysts, BI professions, developers can use AutoML in their familiar tools and experiences Learn how to get started using AutoML for use cases including classification, regression, and forecasting.
SQL Server 2012 with PowerShell V3 Cookbook" is an example-focused book that provides step-by-step instructions on how to accomplish specific SQL Server tasks using PowerShell. Each recipe is followed by an analysis of the steps or design decisions taken, and additional information about the task at hand. Working scripts are provided for all examples so that you can dive in right away. You can read this book sequentially by chapter, or you can pick and choose which topics you need right away, This book is written for the SQL Server database professional (DBA, developer, BI developer) who wants to use PowerShell to automate, integrate, and simplify database tasks. A little bit of scripting background is helpful, but not necessary.
Data Scientists at Work is a collection of interviews with sixteen of the world's most influential and innovative data scientists from across the spectrum of this hot new profession. "Data scientist is the sexiest job in the 21st century," according to the Harvard Business Review. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report. Through incisive in-depth interviews, this book mines the what, how, and why of the practice of data science from the stories, ideas, shop talk, and forecasts of its preeminent practitioners across diverse industries: social network (Yann LeCun, Facebook); professional network (Daniel Tunkelang,...
Decision intelligence (DI) has been widely named as a top technology trend for several years, and Gartner reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies. But until now, there has been little practical guidance for organizations to formalize decision making and integrate their decisions with data. With this book, authors L. Y. Pratt and N. E. Malcolm fill this gap. They present a step-by-step method for integrating technology into decisions that bridge from actions to desired outcomes, with a focus on systems that act in an advisory, human-in-the-loop capacity to decision makers. This handbook addresses three widespread data-driven decision-making problems: How can decision makers use data and technology to ensure desired outcomes? How can technology teams communicate effectively with decision makers to maximize the return on their data and technology investments? How can organizational decision makers assess and improve their decisions over time?
Implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies Key FeaturesLearn advanced concepts in Azure ML and the Cortana Intelligence Suite architectureExplore ML Server using SQL Server and HDInsight capabilitiesImplement various tools in Azure to build and deploy machine learning modelsBook Description Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML pro...