- April 8, 2019 - April 12, 2019
8:00 am - 5:00 pm
Course Length: 5 Days Course Dates: April 8 –12, 2019 Course Venue: Calgary, Alberta, Canada
Data visualization is a dynamic and emerging field which knits together concepts from software engineering, user experience, and design. Visualization, whether scientific or information, is now being used by almost every organization today. Visualization breathes life into engineering, business, financial and textual data. Part art, part science, with implications in the private, government, and non-profit sectors, data visualization leverages its cross-domain origins to translate complex concepts into simple, easily communicated and easily understood information. This course will briefly cover the history of visualization and its relationship to computer graphics, imaging, and visual analytics, review the most common and successful visualizations, discuss advanced visualizations, many integrated with analysis (the new visual analytics). We will also provide an overview of various visualizations systems currently available.
Who Should Attend?
The course is designed for professional reservoir engineers, oil and gas data analysts, petrophysicists, geophysicists, geologists, and asset managers who are interested in understanding what visualization is and its possible role in the oil and gas industry.
What You Will Gain:
By the end of the course, participants should be able to:
- Understand and apply the basic principles of visualization and classic visualization techniques
- Acquire, parse, and analyze abstract data sets
- Design and implement standard data visualizations techniques
- Evaluate a visualization system through examples
- Create browser-based data visualizations
- Introduction to data visualization and terminologies
- Visualization infrastructure (graphics, programming, human perception)
- Basic visualization (charts, plots, animation, interactivity)
- Data driven document (D3)
- Visualizing relationships (determining the information hierarchies, networks)
- Visualizing information (text, databases)