Tableau 2019.1 for Data Scientists [Video]
This is the code repository for Tableau 2019.1 for Data Scientists [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
About the Video Course
You’ve just completed an incredible data science or data analytics project. You still need to present your findings to your manager, client or even a large audience at the conference. In these kinds of situations, powerful visualization can make or break your project. What should you do? With Tableau 2019.1 for Data Scientists, you’ll be able to answer key data decision questions, learn how to deal with disorganized data, and even visualize your results with maps and dashboards. What makes this training module different? This step-by-step guide is designed to give you practical and essential skills that anyone doing data visualization and analytics needs to have. You’ll be able to boost your visualizations by learning techniques such as adding filters and quick filters, and using color schemas in dashboards.
By the end of this course, you’ll have the skills to make your Tableau data visualization projects a success by creating fascinating stories and offering invaluable guidance when strategic business decisions are being made.
What You Will Learn
- Connect Tableau to various datasets and gather data from sources such as Excel and CSV files
- Work with full-suite visuals and create bar charts, area charts, maps and scatterplots, and treemaps and pie charts
- Explore storytelling and how to choose the best colors for your dashboards
- Discover the types of joins and how they work
- Work with data blending in Tableau
- Export results from Tableau into PowerPoint, Word, and other software
- Understand aggregation, granularity, and level of detail
- Study advanced data preparation in Tableau and profit analysis
Instructions and Navigation
Assumed Knowledge
To fully benefit from the coverage included in this course, you will need:
No prior knowledge
Technical Requirements
This course has the following software requirements:
Minimum Hardware Requirements
For successful completion of this course, students will require the computer systems with at least the following:
OS: Windows 7 or higher / Mac OS X 10.7 or higher
Processor: 2 Core
Memory: 8GB
Storage: 15 GB
Recommended Hardware Requirements For an optimal experience with hands-on labs and other practical activities, we recommend the following configuration:
OS: Windows 7 or higher / Mac OS X 10.7 or higher
Processor: 2 Core
Memory: 8GB
Storage: 15 GB
Software Requirements
Operating system:
Browser:
Atom IDE, Latest Version
Node.js LTS 8.9.1 Installed
Tableau 2019.1
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent