Tableau Desktop: Part 2

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Tableau Desktop: Part 2

Coursera · Intermediate ·📊 Data Analytics & Business Intelligence ·3mo ago

Key Takeaways

Analyzes data to find timely insights and gain competitive advantage using Tableau Desktop

Original Description

In today's business environment, data is an abundant raw material, and successful organizations have found ways to extract insights from the data. With the abundance of computational power and storage, organizations and employees with many different roles and responsibilities can benefit from analyzing data to find timely insights and gain competitive advantage. Data-backed visualizations allow anyone to explore, analyze, and report insights and trends from data. Tableau® software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Beyond the fundamental capabilities of creating data-driven visualizations, Tableau allows users to manipulate data with calculations to show insights, make visualizations interactive, and perform statistical analysis. This gives users the ability to create and share data-driven insights with peers, executives, and clients. This course is designed for professionals in a variety of job roles who are currently using Tableau to perform numerical or general data analysis, visualization, and reporting. They need to provide data visualizations from multiple data sources, or combine data to show comparisons, manipulate data through calculations, create interactive visualizations, or create visualizations that showcase insights from statistical analysis. This course is also designed for students who plan to obtain the Tableau Desktop Specialist certification, which requires candidates to pass the Tableau Desktop Specialist exam, or the Tableau Certified Data Analyst certification, which requires candidates to pass the Tableau Certified Data Analyst exam. In this course, you will: connect to and transform data; refine visualizations; analyze data with calculations; perform statistical analysis, forecasting, and predicting; create content; publish and manage content; get answers with Expla
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