Advanced Analytics with R and Tableau

Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of R

Description

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 video course will intensify data skills for data viz-savvy users who want to move into analytics and data science 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. 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 course, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.

About the Authors

Jen Stirrup, recently named as one of the top nine most influential business intelligence female experts in the world by Solutions Review, is a Microsoft Data. Platform MVP, and PASS Director-At-Large, a well-known business intelligence, and data visualization expert, author, data strategist, and community advocate who has been peer-recognized as one of the top 100 most global influential tweeters on big data and analytics topics.

Specialties: business intelligence, Microsoft SQL Server, Tableau, architecture, data, R, Hadoop, and Hive. Jen is passionate about all things data and business intelligence, helping leaders derive value from data. For two decades, Jen has worked as an artificial intelligence and business intelligence consultant, architecting, delivering, and supporting complex enterprise solutions for customers all over the world.

Ruben Oliva Ramos is a computer system engineer from Tecnologico of León Institute with a master’s degree in computer and electronic systems engineering, tele-informatics, and a networking specialization from University of Salle Bajio in Leon, Guanajuato, Mexico. He has more than five years’ experience in developing web applications to control and monitor devices connected with the Arduino and Raspberry Pi using web frameworks and cloud services to build an Internet of Things applications.

He is a mechatronics teacher at the University of Salle Bajio and teaches students studying for their master’s degree in Design and Engineering of Mechatronics Systems. He also works at Centro de Bachillerato Tecnologico Industrial 225 in Leon, Guanajuato, Mexico, teaching electronics, robotics and control, automation, and microcontrollers at Mechatronics Technician Career.

He has worked on consultant and developer projects in areas such as monitoring systems and datalogger data using technologies such as Android, iOS, Windows Phone, Visual Studio, .NET, HTML5, PHP, CSS, Ajax, JavaScript, Angular, ASP .NET databases (SQLite, MongoDB, and MySQL), and web servers (Node.js and IIS). Ruben has done hardware programming on the Arduino, Raspberry Pi, Ethernet Shield, GPS, and GSM/GPRS, ESP8266, control and monitor systems for data acquisition and programming.

He’s the Author of the Pack Publishing book: Internet of Things Programming with JavaScript.

Who is the target audience?
  • This video course 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 course will start off with concrete examples of R and 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 video course.

Full Details : [ Take Course Now ]
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