Identifying data terms can improve cybersecurity efficiency


The time period “knowledge” is imprecise. Figuring out the kinds of knowledge helps corporations defend themselves and higher get well from a cyberattack.

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You might know the place your knowledge is, however do you additionally know what the info consists of? “Think about you are at a celebration. You ask somebody you’ve got simply met what they do for a residing, and so they reply: ‘I work in knowledge,'” stated Sky Cassidy, CEO of MountainTop Information, in an e mail interview. “They could as properly have stated ‘stuff.’ It actually means nothing by itself.”

SEE: Report: SMB’s unprepared to deal with knowledge privateness (TechRepublic Premium)

Cassidy, accustomed to the vagaries of information assortment and its utilization, is on a quest to make sense of what he calls misunderstood knowledge. In addition to lowering confusion, there are cybersecurity-related advantages to understanding greater than “it is knowledge,” particularly when cybercriminals come calling.

Cassidy’s level is that understanding what’s contained in the container known as knowledge is vitally essential to those that use the info and people who handle the info when contemplating knowledge safety. To get everybody on the identical web page when speaking about knowledge, Cassidy makes use of the next classes of information: 

Numbers (quantitative knowledge): That is the commonest class. As a result of numbers are straightforward to research, and, if wanted, create extra pertinent knowledge. An instance may be the making of Key Efficiency Indicators (KPI) from Take a look at Process Specification experiences (Observe: This isn’t the “Completely Pointless Stuff” report made well-known within the film “Workplace Area”). To make this class much less nebulous, Cassidy suggests refraining from calling it merely knowledge, if you end up referring to, for instance, gross sales totals.

SEE: Navigating knowledge privateness (free PDF) (TechRepublic)

Non-numerical knowledge (qualitative knowledge): Cassidy stated if it can’t be represented by numbers it is a good wager the info is qualitative. “The variety of web site visits or leads can be quantitative, however the URLs individuals visited, the timestamp, and different info that’s greater than only a rely is qualitative knowledge,” he stated.

As soon as once more, saying there’s a want for knowledge doesn’t get the job achieved or make mates. It is best to be as descriptive as attainable; for instance, addressing knowledge particular to web site guests is most popular over merely saying “web site knowledge.”  

Massive knowledge: This sort of knowledge consists of very massive units of unstructured knowledge. Cassidy referred to purchasing habits collected by shops for example, which might seemingly embody:

  • What’s purchased?
  • When was it purchased?
  • What was the associated fee?
  • What sort/class of product?
  • Who purchased it?

“The information collected over time on a single shopper by way of their use of a rewards card or one thing comparable wouldn’t be thought-about massive knowledge, however that very same knowledge on each shopper within the US can be massive knowledge,” he stated. “Different examples can be inventory trade site visitors, roadway site visitors patterns, climate knowledge, and the knowledge collected by each app on each cellphone on a regular basis.”

SEE: Information privateness legal guidelines: A mini glossary (TechRepublic)

Darkish knowledge: This class is info that’s created, however seldom, if ever, checked out or used. Cassidy makes use of the examples of all of the billions of photographs or emails saved on-line. “Mainly, the info equal of the whole lot you place in that storage shed since you may want it, however by no means do.”

Database: Though this class appears too broad, Cassidy collapses it into knowledge utilized in direct gross sales and advertising and marketing, additionally known as lists, advertising and marketing lists, gross sales lists, direct advertising and marketing knowledge, marketing campaign lists, or goal lists. “That is the database of prospects or shoppers that features issues like, firm identify, deal with, cellphone quantity, contact identify,” Cassidy stated. “Utilizing ‘database’ moderately than ‘knowledge’ will assist forestall confusion, however it’s endorsed to go even additional and say the kind of database it truly is, similar to gross sales database, advertising and marketing database, or shopper database.”

SEE: Information Privateness Day: 10 specialists give recommendation for shielding what you are promoting (TechRepublic)

Analytics: Cassidy stated analytics just isn’t an information class; it is a course of for analyzing uncooked knowledge with a view to make conclusions about that info, which in a way is transferring from the imprecise time period knowledge to particular elements which have actual worth. As a substitute of web site site visitors info, evaluation can be utilized to find out what services individuals are most interested by, and what adverts are driving essentially the most site visitors.

How does this assist with cybersecurity?

Cassidy’s aim all through has been to level out the necessity to change broad-sweeping phrases, similar to “knowledge,” with particular terminology similar to “customer-contact database.” Doing so lessens the prospect of confusion, and fewer confusion is at all times good. 

Think about an organization with a number of distant areas in the midst of an information breach. If every location was on the identical web page about what particular database was underneath assault, moderately than simply saying knowledge was leaving the constructing, it could slender down the risk. Figuring out the various kinds of knowledge helps the corporate pinpoint precisely what sort of knowledge is compromised and what to do about it.

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