- Introduction to SAS Visual Analytics Environment
- Bar Charts in SAS Visual Analytics
- Pie Charts
- Step Plots
- Heat Maps
- Correlation Matrix
- Word Clouds
- Time Series in SAS Visual Analytics
- Gauge Charts
- Line Charts
- Box Plot
- Butterfly Chart
Practical SAS Visual Analytics is aimed to show examples of data visualization using SAS Visual Analytics, which is one of the leading software in the graphical analytics marketshare. To try this software requires no installation, no configuration and no previous experience. SAS Visual Analytics on SAS Viya is a cloud hosted proprietary software that requires a license to be used, since may 2019 you might be able to access it for free as an independent learner in SAS cloud servers. SAS Visual Analytics works on Linux Servers called LASR servers, it is compiled to handle massive amounts of data distributed across computer clusters. You can access to SAS VA through your web browser. The course will not have a theoretical approach to the statistical background of the charts exhibited along the videos but it it will be more a practical discussion on how-to carry out statistical charts.
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About the instructors
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Machine Learning Engineer
I am a machine learning engineer and a huge part of my career has been involved in commercial banking, insurance and retail industries. In recent years there has been a revolution in the way business are making their decisions. With the growth and the capability to store and process massive amounts of data and aided with the development of ML algorithms we have discover that strategies can be smarter if based on data.
Basically my job is to develop, assess and mantain ML models from countless source of data stored in computer clusters and then propose conclusions based on the output of the algorithm.
I hope the courses in this platform help you to find the motivation and the knowledge required to succeed in your work.
Very informative. Covers all the graphs one can use in depth
Good overview of visualizations available, but most people learn by doing, not watching. This course is all watching; no doing.