RFPs and security questionnaires make the world of sales and procurement go round. They’re both vital tools to help buyers assess potential relationships with vendors and ensure proper criteria are met before entering into any binding contracts. And while they serve an important role in the sales process, the burden they put on buyers and vendors alike has led to the creation of tools to streamline the process for all involved. Can you use a one-size-fits-all solution?
Have you ever received a puzzle as a gift from a well-intentioned friend? They likely thought something along the lines of, “Hey, this person’s into solving problems — I bet they’d love putting together this bad boy on a rainy day.” The sentiment was spot-on. Puzzles are your thing.
The results are in, and Protegrity has officially been named the “Data Security Solution of the Year” by the 2021 Data Breakthrough Awards. Data Breakthrough is an independent market intelligence organization that recognizes the top companies, technologies, and products in the global data technology market today.
As the name implies, dynamic data masking actually masks data. Just as protective masks have obscured people’s smiles (and frowns) during the pandemic, this data-protection method covers sensitive data. People who shouldn’t see the data won’t see it.
Tokenization hides data. Sometimes data must be hidden in order to satisfy compliance requirements and customers’ expectations for data privacy. A form of data protection, tokenization conceals sensitive data elements so should an organization’s data be breached, the visible tokenized data—essentially a replacement for the valuable data—means nothing.A hacker will only see characters that are meaningless.
Spelling, let alone pronouncing, “anonymization” and “pseudonymization” is just the beginning. Vocabulary, however, will be the least of the challenges for organizations that ignore the business value created through the use of these data protection methods. Anonymization and pseudonymization are two ways to de-identify sensitive data, and each has a distinct purpose in the tightrope balance between fully using and fully protecting data and data privacy.
