Cover image of Not All Data Is Created Equal
A short book, almost an extract, from O’Reilly, Not All Data… is readable and useful, but expectedly scant.
I’d expected more of a book on “your data might not be what you think it is”, but this serves as a handy introduction to the risks involving data, for example:
The failure to audit and categorize data can be harmful to a company’s health. “The downside is significant,” says [Chris Moschovitis, an IT governance expert and chief executive officer at tmg-emedia]. In most companies, for example, low-value data far outnumbers mid-value and high-value data. Spending the same amount of money protecting all kinds of data, regardless of its value, can be financially crippling.
“If low-value data assets are distributed across systems, then protecting them with controls designed for higher-value assets violates the basic principle that the value of an asset must exceed the cost of the controls,” he says. “Otherwise, you’re wasting your money.”
This idea is later described as the golden rule of corporate data security, and the book introduces the C-I-A method:
It’s common for CISOs to employ the C-I-A method for managing data risk. In this instance, C-I-A stands for confidentiality, integrity, and availability.
There’s also an interesting twist on the generational divide from Monica Rogati, an independent data science advisor and an equity partner at the Data Collective:
Rogati believes we’re on the verge of a paradigm shift in which “digital natives” are superseded by “data natives.” If she’s right, organizations will have to significantly ramp up their data management skills
The final conclusion is worth pondering:
In retrospect, it seems clear that treating data as some kind of commodity is misguided and dangerous. Data isn’t oil—it’s us. It’s our lives, our behaviors, and our habits. It’s where we go, what we eat, where we live, how much money we earn, which people we like, and which people we don’t like.
We can’t treat data like oil because data is infinitely more precious. A better understanding of data starts by accepting that data, like snow, comes in a variety of forms. And for better or worse, it’s not all created equal.