Data Analytics with Tableau, Python, R, and SQL

• Hands-on experience with data analysis (e.g., using Excel)
• General understanding of database concepts
• No programming experience required

Audience

• Data analysts

Data analytics is the science of analyzing raw data to gain insights and trends. Tableau is a leading business intelligence and data visualization tool, while SQL is the most commonly used language for querying databases. Together with two of the most popular programming languages for data science, Python and R, Tableau and SQL provide a robust, end-to-end solution that can help visualize and analyze data effectively.

This instructor-led, live training (online or onsite) is aimed at data analysts and anyone who is interested to learn how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis.

By the end of this training, participants will be able to:

• Perform data analysis using Python, R, and SQL.
• Create insights through data visualization with Tableau.
• Make data-driven decisions for business operations.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

• Overview of Tableau
• Fundamentals of Python, R, and SQL

Getting Started

• Setting up the development environment
• Understanding software integration

Data Analysis with Python

• Python fundamentals and programming
• Importing libraries and datasets
• Wrangling data
• Data normalization and formatting
• Exploratory data analysis
• Performing regression analysis
• Model development and evaluation
• Visualizing Data

Data Analysis with R

• R fundamentals and programming
• Preparing data
• Classifying and working with data in R
• Using functions
• Visualizing Data

Data Analysis with SQL

• Setting up the database
• Connecting Python and SQL
• Connecting R and SQL
• SQL aggregations and joins
• Querying the database
• Manipulating data

Data Visualization Using Tableau

• Tableau design principles for visualization
• Creating dashboards, charts, and tables
• Mapping techniques
• Regressions in R and Tableau
• Advanced analytics with R and Tableau
• Practical examples and use cases

Troubleshooting

Summary and Next Steps