-: So once you've analyzed your data
and it's time to start thinking about
what you're gonna communicate to an audience,
you have to figure out what you're gonna communicate.
You have to actually look at your data
and decide what's really in there
that's gonna go in your story.
And this is what we usually refer to
as finding the true so what.
What really matters?
What is worth bubbling up to your audience?
Now, most data stories,
not because they should be,
but just they end up being kind of boring,
not very interesting,
because the tendency is,
"Hey, I did all this hard work.
I investigated the data.
Here's all the data."
We just regurgitate everything
we discovered to our audience,
versus actually narrowing it down,
focusing, filtering, to just the most important stuff.
So our goal here is to definitely try to avoid that.
We want to actually bubble up
what is gonna really be compelling for our audiences.
So, part of that is distinguishing
between the interesting and the important.
So you may find all kinds of interesting stuff
in your data set.
All kinds. It's truly interesting.
It's really interesting, new,
something you didn't know before,
whatever the case may be.
But is it actually important?
You may discover something that may lead to another idea.
The question is, is that other idea relevant,
important, or is it just a distraction?
It can be hard to distinguish between those two things.
But generally, you know,
if you really focus on the story you're trying to tell,
the important things you know your audience needs.
Remember the KWYs?
You'll be able to recognize the difference
between important stuff and just interesting stuff.
Now, as part of that,
you have to be certain.
You have to look at it and ask yourself,
"Does my audience really need this?
Is this really important?"
Which also, once again, isn't always quite so clear.
You also may run into a situation
where you come across data,
and maybe you're looking at your data
and you come across the same idea
multiple times in the dataset.
This is true here.
It's true here.
And listen, that may be really important to say,
"Hey every way we looked at the data four times,
we found the same story".
That may be worth saying.
Or, it may just be mildly interesting
that you found something four times,
but the most important thing is
that you found that thing.
Depends on who the audience is.
So if you're telling a story about,
let's say you're investigating cancer rates
in a certain region,
and no matter which way you slice it,
you found high cancer rates in this region
coming at it from 12 different directions.
And you're speaking to an academic audience,
proving an academic point about this research.
You might say that you've found it 12 times.
If you're telling an audience of
like a general newspaper audience let's say, general public,
maybe it's just important to say this thing happened.
Not to talk about all the methodology
and the 12 different ways.
-: So different audience, different needs,
different levels of importance,
different emphasis on what's a true so what
versus maybe just interesting.
You also have to ask yourself, is it clear.
And that's part of that same argument.
So if I'm telling a general audience about
I found these elevated cancer rates in this region,
and I spend 20 minutes going down an rabbit hole
of the 12 different ways I proved it,
they're gonna get lost.
It's not gonna be clear to them.
Again, for an academic audience,
it may be a different situation.
Another question you would ask is,
is there a story here?
So I've figured out what's interesting versus important.
I'm elevating the important stuff.
But if I just throw a bunch of stuff at you,
a bunch of facts, it's just a collection of facts.
When you weave them in together into a narrative,
which we're gonna talk about in the next module,
it's much more impactful on your audience.
So it is part of the true so what
to recognize "Is this important?"
Yes. "Is this relevant?"
Yes. And "Does this fit into a narrative?"
Now, it may be so important,
that even though it does not
fit into your overall narrative,
you cannot avoid talking about it.
Fine. So think about how you're gonna do that
within the context of that narrative you're creating.
At least at a minimum,
say "Hey, here's the narrative I'm telling,
telling, telling, telling a story, story, story.
By the way, this has nothing to do with that,
but this is really important.
I'm gonna say it anyways."
Do that. Just be aware that that's what you're doing.
Just know that you have this other thing
that's not part of your narrative.
Or like I said before,
if it's not part of the narrative,
and the narrative is really focused,
and it's not that level of importance,
maybe it needs to be left out.
Again, this is your decision based
on your audience, what you're doing.
But I want you to think about things like this.
And then also you have to think about
is it aligned with your questions.
This is where we started.
I'm asking questions of my data.
I'm trying to discover something specific.
Now maybe I discover something new
that's not aligned with my questions,
and maybe that takes over the entire project.
Okay, that could happen.
Maybe I'm gonna go off on a tangent
that's more important than this original place.
That's fine. But the point is, once again,
how do you distinguish between important versus interesting?
This is interesting, but does it aligned with my questions?
Which is important?
That's the key thing here today for me now.
If it's not, maybe it's really not important.
Maybe it's some just interesting.
You also, by the way, as part of this process,
can put your findings in rank order.
There is no way,
zero chance I'm gonna leave my data story
without saying this one.
This is the most important insight.
Boy, if I miss this,
I might as well just jump off a cliff.
There's this one, there's this one,
there's this one, there's this one.
Once I get past this line,
these are all nice to have insights
I might share with my audience.
By putting them in rank order,
it makes it easier to do that.
Certainly feel free to literally
just put them in rank order.
And above all,
do all of this in the context of the KWYs.
What is my data saying, obviously,
what does my audience need from me,
and what do I really want to say about it?
Like I said earlier, the KWYs drive every decision, truly.
You're looking at an insight.
You're trying to decide
is this important or interesting?
Does this fit in my story
or can I leave it on the cutting room floor?
What are your KWYs?
Well, my audience really needs to understand X.
Does this have to do with X?
Is this central to X?
Yes. Okay. It goes in the story.
Is this central to X, this one over here?
Hmm. I mean, it's important.
It's kind of interesting.
Okay. Maybe not.
I'll keep saying the same thing over and over again.
I think you all get it.
So we can move on.
And the next thing I'm gonna talk about
is an example of finding a so what.