So what can stories in SAP Analytics Cloud do for you?
Let's look at an example to illustrate.
Suppose you work for,
let's say the office of the financial controller.
Your manager asks you to pull together
some insights into the organization's performance,
so you start by creating a new story.
In SAP Analytics Cloud, a story is
a container object that lets you explore your data and organize your charts,
maps, tables, and other objects to tell a story about your insights.
So what next?
You consider jumping straight into exploring
some data or leveraging machine learning to find
patterns in it or creating a page so you can
get right to visualizing some insights about it.
But maybe you're not sure where to begin,
so you launch Search to Insight.
Search to Insight is a smart feature that uses
natural language questions to dynamically build
visualizations that you can add to your stories.
You ask the system to show you sales revenue,
which brings up some models to choose from.
A model is a representation of data in the system, transformed and
organized to meet the needs of multiple users.
It includes elements such as measures,
which contain quantitative information that can be used for calculations,
dimensions, which are qualitative and helped to provide
context, and versions, which capture different categories of values,
such as actual, budget or forecast, used for planning purposes.
You recognize one of the models.
So you select that and then restrict the results to 2019.
And just like that, you have
your first visualization which you copy to a new responsive page.
A responsive page has lanes that
automatically resize to fit different screens.
So your story works with mobile devices.
While the grid page gives you a spreadsheet format for working with tables.
And a Canvas page is a blank slate that provides
maximum flexibility and control for building content.
Just because it's this easy,
you add variance to the charts,
show the difference between the actual and budget values.
Variance lets you compare values between different measures,
versions or time periods.
Okay, so your story now contains a page,
your first chart, and some data. That was easy, right?
Next, you switch to the explorer to find out what else is in that data set.
Data exploration mode, or the Explorer, provides a faceted view of your data
so you can dynamically generate visualizations. Here
you can see all the measures from the model
along with the dimension used in your last querys
so you create another chart show gross margin for Q1 of 2019,
and add that to the page as well.
And now that you're getting into the zone,
you crank out a few more numeric point charts,
to highlight a bunch of Key Performance Indicators,
arrange everything so it's easy to see at
a glance, and pop in a logo to make it look super professional.
Okay, now you're getting somewhere!
Next, you use the Designer panel to build
a more complex chart that shows sales revenue over time...
with color-coding for each version of the data.
You want to see the results by quarter for 2018 and 2019,
so you apply filter.
Once you see the finished chart,
you realize that this type of chart would
be really useful to show several KPIs,
so you remove the existing measure and replace it with a measure input control.
Basic input controls let you and your colleagues choose which
dimension members display across multiple visualizations,
while measure and dimension input controls enable you to
choose which measures or dimensions display in a single chart.
Here, you want users to be able to choose sales revenue,
operating expenses, gross margin, or operating income.
You add other charts too, from a variety of
models, and some other objects that provide more context,
so you have a complete overview of
the organization's performance, and then rename your page accordingly.
So, you might be thinking "Is that it?" Not even close...
Now you want to dig down into a geographical analysis of the data,
so you add a new page to help tell
everyone that you've moved onto the next part of the story.
Here you add a geo map that shows whether
specific countries are on plan in terms of sales revenue.
You also add some input controls,
so you and your colleagues can focus on specific time periods,
regions, and product types,
and a chart that shows the same information in a different way.
Some people might stop there, but you're still not done.
You set up linked analysis, so that making
a selection on the map updates the chart accordingly.
And finally, let's not forget that your office is all about financial planning,
so you add another page to move the story onto the next topic.
Here, you add a value driver tree, so you
can explore what-if scenarios, like how an increase in
the sales promotions would impact total operating expenses.
You also add a table where users can adjust plan values.
And, just put a cherry on the top,
you throw in a few more charts for
more context before firing it off to your manager for approval.
And there you have it,
a multi-page story that provides
all the information needed to make great decisions,
and you barely broke a sweat.
Ready to try it for yourself?
Start your free trial of SAP Analytics Cloud today.