Data Management: Data Backup, Security, and Cleaning

The Rule of Three

• Make 3 copies (e.g. original + external/local + external/remote)

• Copies should be geographically distributed (local vs. remote) if possible

Backup Options 

• Computers and work station hard drives, external hard drives, university servers

• CDs and DVDs are not recommended 

• Cloud Storage

• Unencrypted security is ideal for storing your data so that you and others can easily read it, but if encryption is required because of sensitive data:
  • Keep passwords and keys on paper (multiple copies) and in a encrypted digital file.
  • Don't rely on 3rd party encryption alone.  
• Store files uncompressed whenever possible. Limit compression to 3rd copy if necessary for storage constraints.
• Retrieve and read data files periodically to test proper working of backup systems.

Data cleaning is the process of detecting, diagnosing, and editing faulty data.
There are several tools and software programs available to facilitate data cleaning and analysis:

OpenRefine is a  free, open source tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.

Tabula is a free, open source tool allowing users to extract data tables from PDFs and convert them into spreadsheets. 

R is a free, open-source programming language that can be useful for data analysis in a variety of ways, from statistical analysis to data visualization.

Python is a general purpose programming language that can perform a variety of functions.

 SPSS Statistics is a powerful statistical software platform.

• SPSS is available for use on eight desktop computing stations at Briggs Library.
• SPSS is also available also to SDSU Faculty, Staff, and Graduate Students employed by the university though SDState IT Support Center.
  (You must be logged-in to request use.)