Tableau 2019.1 for Data Scientists [Video]

More Information
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
About

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.

All the code and supporting files for this course are available at: https://github.com/PacktPublishing/Tableau-2019.1-for-Data-Scientists

Style and Approach

This course begins with Tableau basics. You will install the software, connect to the data file, and export worksheet. Even beginners will feel completely confident and ready to leverage Tableau fully. The approach in this course is to get just enough theory and immediately implement it in real-life exercises and quizzes. Every section of this training course is independent, so you can start in whatever section you wish, and you can do as much as you like.

Features
  • Create impactful data science and analytics visualizations including Sankey diagrams and presentations
  • Analyze your data with Tableau and challenge yourself by working with new datasets and real-life exercises
  • Cover the latest Tableau 2019.1 features to hone your visualization skills
Course Length 2 hours 51 minutes
ISBN 9781789958249
Date Of Publication 28 Feb 2019

Authors

Manja Bogicevic

Manja Bogicevic’s mission is to help decision-makers gain more profit with machine learning insights. She is one of the first self-made women data science entrepreneurs in the world. Currently, she is pursuing her Micromasters at MIT (field: Data Science & Statistics). She finished an MBA (Leader Project) at Ivey Business School in London, Canada, and a BA at Faculty of Economics in Belgrade, Serbia. She helps Investors and Asset Managers with data and insights on the flow and behavior of institutional investors in emerging markets. It’s a niche area, of serious interest to only around 1000 people in the world.

Manja is a Data Science Mentor at VC fund Faster Capital from Dubai and Data Scientist Leader and Shareholder at Trounceflow from London. Currently she works as a Data Scientist on projects in the marketing, FinTech, and sports industries.

She is a data Science blogger for Cambridge Spark, Towards Data Science, Data Driven Investor, and Becoming Human: Artificial Intelligence Magazine. She is also the creator and teacher of the course “How to become Data Scientist in 6 months”, with more than 300 students from Serbia.

Manja has a strong interest in projects that require both conceptual and analytical thinking. Her strong economics and business background in combination with her technical skills, which delivers innovative and actionable data science solutions in business.

She makes magic in the Data Science world with Python, SQL, Machine Learning algorithms, and Tableau.