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Coursera

Data Analysis with Tableau

Tableau via Coursera

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Overview

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The Data Analysis with Tableau Course will teach you how to manipulate and prepare data for analysis and reporting. You will also learn how to use the analytics features in Tableau to more effectively calculate analytics versus manual calculations. In this course, you will perform exploratory data analysis as well as create reports using descriptive statistics and visualizations. This course is for anyone who is curious about entry-level roles that demand fundamental Tableau skills, such as business intelligence analyst or data reporting analyst roles. It is recommended (but not required) that you have some experience with Tableau Public, but even if you're new to Tableau Public, you can still be successful in this program. By the end of the course, you will be able to: -Apply Tableau Public techniques to manipulate and prepare data for analysis. -Perform exploratory data analysis using Tableau and report insights using descriptive statistics and visualizations. -Identify the benefits of the analytics feature in Tableau by utilizing this tool versus manually calculating the analytics.

Syllabus

  • Data Analysis and Exploration
    • Welcome to Data Analysis with Tableau, the seventh course in the Tableau Business Intelligence Analyst Professional Certificate series. In this first week, we introduce you to the Tableau Data Analysis Process framework. This comprehensive guide is essential for effectively preparing, analyzing, interpreting, and communicating data. You'll also begin learning about data exploration, which helps you dive into datasets and refine them for more insightful analysis.
  • Data Preprocessing and Aggregation
    • Welcome to Week 2 of Data Analysis with Tableau, where you will dive deeper into the crucial stages of data preparation. This week focuses on refining your skills in preparing data for in-depth analysis. Building upon the preprocessing concepts introduced in previous courses, you will explore advanced preprocessing techniques to enhance the quality and relevance of your data. Additionally, this week is dedicated to understanding and utilizing the powerful aggregation tools integrated within Tableau.
  • Introduction to Statistical Analysis
    • Welcome to the third week of Data Analysis with Tableau! This week, you will engage with external modules to deepen your understanding of data distributions and variation for data comparisons. You'll explore fundamental statistical concepts including mean, variance, standard deviation, as well as frequency and population distributions, continuous distributions, hypothesis testing, and confidence intervals. After completing the external modules, you will learn how to create and interpret histograms and box plots in Tableau, turning your newly acquired statistical knowledge into valuable visualizations. By the end of this module, you will not only comprehend the underlying principles of statistical analysis but also be adept at visually representing statistical data.
  • Introduction to Predictive Analytics
    • Welcome to the fourth and final week of Data Analysis with Tableau! This week begins with an external module on correlation and regression, which are key for understanding predictive trends. You'll then apply these concepts in Tableau by creating and interpreting scatter plots and enhancing visualizations with reference lines, bands, and trend lines. The week culminates in a comprehensive project using the Superstore dataset, where you'll apply not only predictive analytics techniques but also integrate concepts learned in previous weeks.

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Tableau Instructor

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4.1 rating at Coursera based on 24 ratings

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