SAS - 1. Starting with SAS ... How to Install University edition?

This is my first post in series of SAS posts I am going to write in coming days.

Here, we are just setting up SAS environment. It is very easy and quick to install and use SAS but if someone has not followed proper steps it will go wrong & one cannot figure it out. Only option remains will be start again from zero.

To learn basic SAS programming SAS University has provided SAS university edition. This is available as virtual machine for which we should have virtualization software like oracle virtual box or VMware.

Follow below steps to do the setup -

1. Download SAS University Edition

https://www.sas.com/en_in/software/university-edition.html

2. Download Virtualization software like VMware or oracle virtual box

https://www.virtualbox.org/

http://www.vmware.com/products/workstation/workstation-evaluation.html

3. Open VMware and provide downloaded virtual machine path to start with

4. After this virtual machine will get started and we will have url to access SAS studio

5. Open URL in browser and Click Start SAS Studio to get into SAS environment

6. Finally we will be having following screen in SAS 9.4 version

Problems may occur & solutions to them –

  1. One might get error as zip is corrupted

  2. Do the fresh download of the SAS university edition and use it.

  3. Localhost:10080 refused to connect

Follow the following checklist to endure that you are doing proper installation as below –

  • Make sure that host file has proper mapping for localhost

  • Make sure that visrtualization is enabled in BIOS option

  • Check network adapter is enabled

  • Use licensed copy of VMware

You can also refer https://www.tutorialspoint.com/sas/sas_environment.htm for details.


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✔ 13+ years of experience in the Software Industry; Over 6.5+ years of experience in machine learning and deep learning projects.


✔ Hands-on Data Science practitioner; a Leading team of data scientists, Python developers, UI developers, and business analysts for multi-million dollar projects


✔ Designed and developed DevOps enabled MLOPs strategy and components from scratch which had saved 80% data annotation and 40% development time for clients.

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