Coursera

Advanced Data Visualization with Tableau (Coursera)

Offered by SkillUp EdTech,
Advanced Data Visualization with Tableau (Coursera)

This advanced Tableau course covers a broad variety of topics to provide you with advanced analytics and data visualization skills. The course walks you through connecting Tableau to SQL databases, creating data linkages, and creating hierarchies for effective analysis, starting with data connectivity and modeling.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

You will work with sophisticated modeling approaches, execute computations, and optimize data models for performance. The course has a strong emphasis on controlling data granularity, utilizing calculated fields, and investigating expressions for ‘Level of Detail’ in complicated analytics.
Topics include effective data transfer, tooltips, hierarchical navigation, and creating user-friendly interfaces. By incorporating interactivity through actions and linking between dashboards, you’ll create seamless data journeys that empower users to explore and analyze information effortlessly.
Throughout the course, you will have opportunities to practice what you have learned. Hands-on labs and projects are inspired from real-world scenarios, to equip you with the advanced, practical Tableau skills that employers seek in today’s job market.
This course is part of the IBM Business Intelligence (BI) Analyst Professional Certificate.

What you'll learn

  • Apply advanced techniques to create interactive and dynamic visualizations in Tableau, demonstrating high proficiency in data presentation
  • Create interactive dashboards in Tableau, incorporating navigation, links between story points, and advanced features such as actions and tooltips
  • Demonstrate a comprehensive understanding of Tableau's capabilities and features such as advanced formatting, dashboard design and web objects
  • Effectively use Tableau’s features to deliver insightful dashboards and stories for data exploration and monitoring

Syllabus

Data Sources, Data Modeling, and Advanced Analytics
In this module, you will learn to elevate your business analysis capabilities by using the full potential of Tableau’s diverse data connectivity features. You will learn about Tableau’s connectivity features and gain insights into business operations across diverse platforms. Learn to track performance metrics, analyze customer behavior, and optimize operational efficiency for informed decision-making. You will explore Tableau’s data relationship capabilities to seamlessly integrate and compare data sets, enhancing your ability to derive valuable insights. Use data model optimization techniques for efficient calculations and a smoother user experience, elevating the effectiveness of your data analysis processes. Additionally, you will gain skills to combine data from various sources, identify trends, and make informed decisions, all while optimizing performance in data analysis and dashboard design. Through hands-on exercises and practical applications, you will learn to seamlessly integrate data from various sources, enabling comprehensive insights into business operations and informed decision-making.

Advanced Formatting and User Experience
In this module, you will learn how to format data and create a visualization for a better user experience. In lesson 1, you will explore advanced formatting techniques and tooltips. The formatting techniques include fonts, colors, shapes, images, layout, and text objects. With advanced formatting, you will also learn to customize your layouts to make them easy to view on any device. Next, you will delve into tooltips and their application to data insights. Tooltips also help enhance the user experience. In lesson 2, you will learn to create a story using Tableau features such as formatting, layouts, and tooltips. A story comprises story points, dashboards, graphs, and maps. You will explore ways to share these stories and dashboards securely with your stakeholders. Lastly, you will learn to choose a secure sharing option based on certain factors.

Final Project and Final Quiz
In this module, you’ll complete a final project where you’ll apply the knowledge and skills you’ve learned throughout the course to complete a data visualization project from start to finish. Then, you will complete the final quiz to validate your knowledge.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Reproducible Research (Coursera) Coursera
Johns Hopkins University

Reproducible Research (Coursera)

Statistics & Data Analysis Data Science

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations.

Jun 15th 2026
4 Weeks
Data Analysis Data Science Reproducible Research
Details
Data-driven Decision Making (Coursera) Coursera
PwC

Data-driven Decision Making (Coursera)

Statistics & Data Analysis Data Science

Welcome to Data-driven Decision Making. In this course, you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used. You'll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used. Finally, you'll have a chance to put your knowledge to work in a simulated business setting. This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017.

Jun 15th 2026
4 Weeks
Business Big Data Data Analysis
Details
Data Science in Real Life (Coursera) Coursera
Johns Hopkins University

Data Science in Real Life (Coursera)

Management & Leadership Statistics & Data Analysis

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses.

Jun 15th 2026
1 Week
Statistics Machine Learning Data Management
Details
Fundamentals of Visualization with Tableau (Coursera) Coursera
University of California, Davis

Fundamentals of Visualization with Tableau (Coursera)

Statistics & Data Analysis Data Science

In this first course of the specialization, you will discover just what data visualization is, and how we can use it to better see and understand data. Using Tableau, we’ll examine the fundamental concepts of data visualization and explore the Tableau interface, identifying and applying the various tools Tableau has to offer.

Jun 15th 2026
4 Weeks
Data Visualization Tableau Data Analytics
Details
Ask Questions to Make Data-Driven Decisions (Coursera) Coursera
Google

Ask Questions to Make Data-Driven Decisions (Coursera)

Statistics & Data Analysis Data Science

This is the second course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. You’ll build on your understanding of the topics that were introduced in the first Google Data Analytics Certificate course. The material will help you learn how to ask effective questions to make data-driven decisions, while connecting with stakeholders’ needs. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Jun 16th 2026
4 Weeks
Spreadsheets Data Analysis Decision Making
Details
Foundations: Data, Data, Everywhere (Coursera) Coursera
Google

Foundations: Data, Data, Everywhere (Coursera)

Statistics & Data Analysis Data Science

This is the first course in the Google Data Analytics Certificate. These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. In this course, you’ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it’s designed to give you an overview of what’s to come in the Google Data Analytics Certificate. Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Jun 16th 2026
5-12 Weeks
Data SQL Spreadsheets
Details
Dealing With Missing Data (Coursera) Coursera
University of Maryland, College Park

Dealing With Missing Data (Coursera)

Statistics & Data Analysis Data Science

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®.

Jun 15th 2026
4 Weeks
Data Analysis Data Collection SAS
Details
Machine Learning Foundations: A Case Study Approach (Coursera) Coursera
University of Washington

Machine Learning Foundations: A Case Study Approach (Coursera)

Statistics & Data Analysis Data Science

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies.

Jun 15th 2026
5-12 Weeks
Python Machine Learning Clustering
Details
Meaningful Marketing Insights (Coursera) Coursera
Emory University

Meaningful Marketing Insights (Coursera)

Marketing & Communication Business

With marketers are poised to be the largest users of data within the organization, there is a need to make sense of the variety of consumer data that the organization collects. Surveys, transaction histories and billing records can all provide insight into consumers’ future behavior, provided that they are interpreted correctly. In Introduction to Marketing Analytics, we introduce the tools that learners will need to convert raw data into marketing insights. The included exercises are conducted using Microsoft Excel, ensuring that learners will have the tools they need to extract information from the data available to them.

Jun 15th 2026
5-12 Weeks
Marketing Data Analysis Microsoft Excel
Details
Python Project for Data Science (Coursera) Coursera
IBM

Python Project for Data Science (Coursera)

Statistics & Data Analysis Data Science

This mini-course is intended to for you to demonstrate foundational Python skills for working with data. The completion of this course involves working on a hands-on project where you will develop a simple dashboard using Python. This course is part of the IBM Data Science Professional Certificate and the IBM Data Analytics Professional Certificate.

Jun 18th 2026
1 Week
Python IPython Data Analysis
Details