Overview
Python is the most popular programming language for data science and machine learning. SQL is the most commonly used tool for database management while Tableau is a leading business intelligence and data visualization tool. Combining SQL, Python, and Tableau provides a powerful, end-to-end solution for data analysis.
This instructor-led, live training (online or onsite) is aimed at data scientists and developers who wish to use and integrate SQL, Python, and Tableau to perform complex data analysis, processing, and visualization.
By the end of this training, participants will be able to:
- Set up the necessary environment to perform data analysis with SQL, Python, and Tableau.
- Understand the key concepts of software integration (data, servers, clients, APIs, endpoints, etc.).
- Get a refresher on the fundamentals of Python and SQL.
- Perform data pre-processing techniques in Python.
- Learn how to connect Python and SQL for data analysis.
- Create insightful data visualizations and charts with Tableau.
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.
Requirements
- Familiarity with SQL concepts and Tableau
- Python programming experience
Audience
- Data scientists
- Developers
Course Outline
Introduction
- The fundamentals of Python and SQL
- Overview of Tableau features and architecture
Getting Started
- Setting up the development environment
- Understanding software integration
Data Pre-processing in Python
- Importing libraries and datasets
- Handling missing data values
- Data normalization and formatting
- Performing regression analysis
Data Analysis with SQL
- Setting up the database
- Connecting Python and SQL
- Querying the database
- Manipulating data (filtering, sorting, and grouping)
Data Visualization using Tableau
- Design principles for visualization in Tableau
- Creating dashboards, charts, tables, and mapping
- Practical examples and use cases
Troubleshooting
Summary and Next Steps