Recap
In the first post of this blog I challenged my readers to explain the data profession to a 5 year old.
In this post I will provide a solution to that challenge. I will build off of everything I’ve covered in this blog. Including:
The Occam’s Data definition for data; so simple a 5 year old would get it
How thinking clearly is a core data skill
Why we need a simpler way to communicate and understand data
Why This Matters
“Adults are just outdated children.” — Dr. Seuss
Do we actually need to explain the data profession to a 5 year old? Maybe - but that is not why we need to be able to do this.
We want people to understand data better. We can improve overall understanding by simplifying. If you are a data professional, you need to be able to explain data simply. If you are new to the data profession, you need a simpler explanation to understand.
What better way to simplify than trying to explain things to a 5 year old?
Think Like A 5 Year Old
Let’s start with the most common question a child receives.
What Do You Want To Be When You Grow Up?
How is it that children at this age are able to answer this question? Probably because they have some exposure to some professions. Either from meeting them or seeing them on a TV show. They know what these professions are because they understand what they do.
Let’s look at some common answers to the most common question:
Doctor - Helps people feel better
Fireman - Puts out fires
Policeman - Protects the community
Librarian - Helps people find books
Scientist - Does experiments and discovers things
Two of these professions in particular, the librarian and the scientist, have similar responsibilities to the data professional. We can use the descriptions of these careers to explain what a data professional is to a 5 year old.
This makes sense when we clarify what librarians and scientists do. We clarify things by taking some time to think.
Librarian Responsibilities
Librarians know how to find books.
They put books where they belong.
They enforce an environment of quiet and focus.
They require borrowers to treat books with respect.
They likely have expertise on specific books.
Scientist Responsibilities
A scientist examines the physical world with curiosity.
They ask questions about the world.
They answer questions by running experiments.
They interpret findings through logical reasoning.
The Two Types of Data Professional
The data profession is a combination of a librarian and a scientist. Some data professions are more librarian, others are more scientist. This becomes clear when we blend the descriptions above with the Occam’s Data definition for data; information.
We can classify the data profession into two sub-roles, each with their own responsibilities.
Information Librarian
Knows where to find an organization’s information.
Keeps this information organized.
Enforce information clarity and focus.
Require respect for integrity of the information.
May have expertise on specific information.
Information Scientist
Examines an organization’s information with curiosity.
This curiosity leads to questions.
Explore and experiment with this information.
Uses logical reasoning to generate findings and insights for the organization.
These responsibilities are simple. You don’t need to know anything about math or computers to understand them. They communicate the value of a data professional. They do this without any confusing technical details.
That said, they are still too difficult for a 5 year old. We can make these definitions even simpler.
The following definition captures all the information in the breakdown above in one sentence.
The Simplest Definition
This is Occam’s Data’s definition for a Data Professional.
A data professional organizes and interprets information.
And to be honest - it’s mostly organizing. But i’ll save that for another post.
Exercise
Try to use this definition.
If you’re a data professional, use it to explain your role. Think of this definition when you start a new project.
If you’re new to data, think of this definition as you’re learning.
And of course write me to let me know how this goes.
This is a great way to explain it! At the end of the day, data is just a fancy word for information.