Event Details
This workshop is for those interested in utilizing Tableau software to create data visualizations and tell stories from transactional data that highlight customer insights and business implications. No prior experience with Tableau software is necessary, you will be introduced to Tableau’s suite of software products and learn how to start using Tableau Prep and Tableau Desktop. In this introductory workshop, you will create data visualizations and dashboards in Tableau Desktop using spatial and aspatial transactional data. Successful examples of Tableau software being used to tell stories about customer behaviour will be reviewed. Best practices for preparing transactional data and identifying customer insights will be discussed.
The workshop will be hands on and consist of a case study project, software demo, group discussion and a handout that will be provided in advance and referenced throughout the session. For the project component, you will create a personalized case study by choosing from a provided list of markets (cities) and business problems to work on. You will have the opportunity to optionally share your work and get feedback from other participants in the workshop.
- Sunday — November 01, 2020
9:00AM - 11:00AM - Virtual
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The Organizer
Research Methods and Data Science Meetup
This Research Methods and Data Science (RMDS) meetup group is devoted to make big data & AI useful, and to promote big data technologies. It is a meet-up group bringing together people from research methodology, data science, data professional services, AI and computing in the greater Los Angeles area.
The focus of the group is about utilizing big data & AI technologies to improve data analytics & research for social good, and to promote research methods and data science innovation. On a regular base, we run workshops on big data analytics that can be applied to model and visualize open data and other complicated big data sets. Also, we will organize special meetings to discuss special data science projects, as well as data science automation and augmentation.