3. Introduction
•Data protection is a critical component
of the analytics business and it is
sometimes a requirement for
companies in certain countries where
information laws are very strict.
•Data Protection Act 1998 (UK)
•EC directive 94/95(EU)
•HIPEA (US).
4. Why data masking is
important?
•To ensure that sensitive information are not leaked
and used by unauthorized parties in possibly illegal
activities, it is essential that protection in the form of
data masking be applied to all data.
•Data masking makes it more difficult for
unauthorized parties who might have accessed the
data illegally to obtain critical information.
•Data masking also allow companies which require
analytics services to be sure that their data will not
be used by the service providers for other
purposes.
5. Nullification
•Nullification is the process of neutralizing
certain sections of the data by way of
substituting the information with a single null
value.
•Usually the null value used is X or an empty
space, but there are other choices.
•Below is a snapshot of a code that does
nullification.
7. Substitution
•Substitution is the process of replacing a
section of the information with pseudo
information.
•Usually a fixed length of the information will
be replaced a randomly generated number;
this number is fixed throughout for all the
values.
•Below is a code showing how this is done.
9. Encryption
•Encryption is the process of masking
the information via an algorithm that
renders it impossible to retrieve the
original information without the key.
•The original information is usually
transformed by a bit operation with a
key.
•Below is a snapshot of the code.
11. Conclusion
•Data masking is a simple and yet
crucial process in data warehousing
and analytics.
•SAS provides many different options
for users who wish to mask their data.
Editor's Notes
In today’s presentation, we will go through several aspects of data privacy as well as the purpose of data masking.
We will discuss the various techniques of data masking as well as how they can be implemented in SAS.
Ever since the beginning of analytics, the industry has been plagued by data issues ranging from poor data quality to privacy issues.
Since privacy is highly valued, several countries have implemented data protection measures to protect data collected.
Several acts have been passed to enforce these measures.
Such protection is critical to protecting the consumer rights.
However, they can be quite nasty to companies who rely on consumer data.
To overcome this, it is important to have methods to mask the sensitive information.
Why is data masking important?
Protecting your clients
Makes outsourcing safer
Illegal access to sensitive data will not compromise the privacy of the clients
Adhering to the data protection acts of the various countries
There are many methods to do data masking
Nullification, Substitution and Encryption are some of the most common methods