Now You See It: Visual Data Analysis
Ninety percent of all business data analysis can be done using simple graphing techniques to discern meaningful patterns in data. The remaining 10%, which requires sophisticated statistical and financial analysis skills, are well addressed by available resources, but where are the resources that teach the skills needed by the rest of us? Even though these skills are easy to learn and apply with proper guidance, very few people involved in analyzing business data know them. This workshop provides a solution.
This course is intended for all those whose work requires them to make sense of quantitative business data. This audience is much broader than financial analysts, or even analysts by any name. This course provides practical skills that are useful to managers at all levels and to anyone interested in keeping a keen eye on the business. Anyone who uses Excel or any of the many other business productivity tools used for data access, analysis, and reporting, will learn how to use them productively, perhaps for the first time.
You will learn to:
- Understand each of the prominent quantitative relationships and the stories they have to tell (time-series, distribution, correlation, etc.)
- Use the best graphs, visual analysis techniques, and practices for analyzing each type of quantitative relationship
- Recognize the visual characteristics of data that are meaningful
- Navigate through data analytically and efficiently
- Apply the findings of information visualization research to the analysis of business data
This course covers:
- An introduction to visual data analysis
- The traits of top data analysts
- The best data for meaningful analysis
- Visual perception and data visualization
- Visual characteristics to look for in the data
- Quantitative business analysis techniques by type including: Analysis of time series, rankings, parts-to-whole, deviations, distributions, correlations, multivariate profiles, and geo-spatial data.
- Analytical navigation
- The critical contributions from the information visualization research community
If you're trying to convince someone (such as your boss) that it's worth your while to attend this course, the article "The Power of Visual Analytics" might be useful.