Data Visualization Solutions for Beginners [Video]

More Information
Learn
  • Understand data types from the perspective of visualization
  • See the explanatory and exploratory types of visualization and their respective stakeholders
  • Explore the uses of colors, hue, and size
  • See type of graphs and know when to use them based on type of data at hand
  • Interpret visualizations using open source tools such as R and Python
  • Get acquainted with Tableau and get a deeper understanding of drill-down analysis
  • Create and present interactive storyboards
About

Data visualization has become very important due to the increase in processing power and organizations being able to unlock their data from jail. It has become the best way to report results and findings to your audience in the most simple and gripping way. However, there is a shortage of visualization experts who can use various tools to explain to stakeholders not just historical data, but also the machine learning results.

In this course, we’ll be using tools such as Tableau, which is the best visualization tool as ranked by the Gartner Report 2017, as well as open source tools such as R and Python to understand data and share findings between fellow data scientists.

This course takes you gradually from basic, fundamental topics to advanced topics with a ton of examples. It also focuses on making you independent of these tools, so you can carry forward your visualization knowledge to any other tool you may need to use. We cover three tools in visualization, namely R, Python, and Tableau and setting up your basic framework for any project you take up. By the end of this course, you’ll have the fundamentals in place, so you can make visualizations on your own with the correct use of various visualization elements.

Style and Approach

This course moves gradually from the basics to advanced, and includes tons of example to get you familiar with vis and help you quickly make your own, while covering common problems that individuals new to this field encounter.

Features
  • Know which kind of graph to use depending on your data, and make your data speak through visualizations to help businesses drive their decisions
  • Unlock deeper level insights using drill-down analysis in Tableau, and apply the skills learned throughout the course using packages such as Seaborn in Python on real-life data from platforms such as UCI data repository
  • Advance your knowledge in data visualization in just 2 hours with tips and tricks at every stage
Course Length 4 hours
ISBN 9781788395786
Date Of Publication 15 Jan 2018

Authors

Mohammed Topiwalla

Mohammed Topiwalla is currently working as a Data Analyst at Servify. Prior to this, he worked at Tech Mahindra and has graduated from Narsee Monjee College with a degree in Information Technology. He has also completed a postgraduate diploma in data analytics from S. P. Jain.

Mohammed often wondered how something as simple as a phone’s sensor can explain to us everything about a user’s activities and how a visualization could explain to a business user everything that there is about their business with some amazing insights in under 5 minutes. This made him switch to the amazing world of data science and visualization. Having worked with some talented people in this field, Mohammed finds it amazing, as the end results are always solutions that could impact many lives and make them a bit easier.

Mohammed is also interested in Artificial intelligence, Neural Networks, and IoT. He is also skilled at writing Python scripts for ingestion into a big data system from production environments, Dev Ops, and creating Android Applications and WordPress websites. Mohammed believes that a visualization artist is only good if they have the capability to explain their visualization to a layman flawlessly. This skill is something he excels in, making him a strong candidate to not just explain how to make a powerful visualization, but how to make a visualization independent of any tool.

When he’s not working, Mohammed loves to meet new people and learn new things. He actively blogs at https://datascience52.wordpress.com/.

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