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Hi again!
Let's pick up where we left off in our second video
of our Getting Started Series,
the sample story.
The visualizations that we explored in this story
may seem a little complicated.
You'll remember that we were able to
drill down to different levels of detail in our charts,
and isolate specific information.
But might be surprised to know
that the entire sample story
was created from data contained in simple spreadsheets.
How does this even work?
Well, to take your data from here to here,
you're going to need a model.
And no, we're not talking about me on a runway,
we're talking about data models.
Models transform your raw data
into useful information
that you can then use to make dynamic visualizations.
In Analytics Cloud the most basic type of models have two things:
measure and dimensions.
But what are those?
Measure are numeric values that can support mathematical calculations.
A measure could be your business revenue, quantities of items, and overall gross margin.
Dimensions can be either numeric or text.
They're descriptive and don't make sense when they're added together.
like phone number or zip codes.
How do measures and dimensions show up in visualizations?
Let's go back to our sample story for an example.
By selecting the measure "net revenue" we see the data as a single numeric point.
But, what if we want to know "net revenue" per "location"?
To accomplish this, we'll add a dimension.
In this case, "location".
Now we have a better understanding of our revenue distribution.
Without defining measures and dimensions in our data, we wouldn't be able to create this chart.
So models are very important.
As you may have guessed, creating a model is called modeling,
and there are two ways to do that in Analytics Cloud.
The first way, is by using The Modeler.
It's a more advanced tool, so if you're new to data modeling it might take some time to learn.
That's why in many organizations, the types of people who use it
are usually data experts. Like those who work in IT.
To acces The Modeler just click "create" and then "model" from the menu.
Because The Modeler is more advanced,
In this video, I'm going to show you the other way to create a model
by adding data directly to your story.
If you haven't already, download the sample data file that's on this page so you can follow along.
Don't worry, I'll wait.
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Ready? Okay.
After you've logged into your trial account
go to the menu and choose "create" - "story".
The first thing we'll do is choose how to start our story.
We'll start by importing and exploring our data.
With the 30-day trial we have the option to add data to our story by
choosing an existing model
by importing a file
or by connecting to Google Drive
Our sample data set is a basic .csv file
so let's choose the "import a file" option.
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Once our data is imported
it displays in a familiar row and column format.
Just like in any spreadsheet, each row represents an individual transaction.
and each cell contains the transactional details.
You may notice that some symbols have been added to the headers here.
Do you remember what they mean?
These symbols let us know that each column has either been identified as a measure
or as a dimension.
Analytics Cloud is pretty smart,
and your columns are probably already defined correctly.
But if you need to, you can change the column type in the "details" panel.
There are some more things you can do with your data at this point
But let's say we're happy for now.
By switching to "Data Exploration" view
our model is created.
And we can start exploring measure and dimensions through visualizations.
If you want to make changes to your model
you can switch back to "Data Manipulation" view like this.
and that's it.
So now we know what a model is
and how easy it is to create one by adding data directly to your story.
Right now this model can only be used within this story.
But, if you want to use it in other stories, or let others use it in theirs, just publish it.
Great, let's save this story as "My First Story" so we can come back and work on it in the next video.
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