This four-part presentation series will comprise of four integral chapters that will solidify your foundation in SAP’s Analytics Cloud.
Also, the tutorial is presented in the forms of GIFS. So, I recommend you to click on the link to see the GIF in action.
a)Creating your first story.
b) Linked Analysis.
c) Geo Maps.
d) Integration of R with SAP Analytics Cloud.
In this segment, we will get a fair understanding on why we need data visualization and the very basics of creating a story with SAP’s Analytics Cloud.
Pre-requisites : Absolutely nothing, other than an internet connection, and an account in SAP Analytics Cloud, which could be accessed by clicking on the link below :
For those of you who have stumbled upon the blog out of curiosity, you may ask — why data visualization ? How is it going to help you in anyway ?
Data visualization is essential solely because it makes ‘understanding’ easier. We have been using data visualizations in physical format for time immemorial. For instance, the first Map was created with the objective of understanding where we are, and where others are, with simple co-ordinates, namely latitudes and longitudes.
As time progressed, and things went digital, a lot more valuable insights can be derived from visualizing the data. It can be used for all purposes- for practical, for commercial, for competitive or for merely personal purposes. The applications may range from analyzing your Sports team’s performances to even identifying your most valuable customers in the retail industry, or if you’re creative enough, you can take the data from your fitness devices to analyze your sleeping patterns. The best visualization tools make ‘understanding’ easier, and one such tool that I will talk about is SAP’s Analytics Cloud, which is a relatively new tool from SAP.
So let’s get started with our first story !
There are two ways to get started with creating a story. A very simple way is to simply drag and drop your data set from the excel file into the SAP Analytics’ home page. The other is to follow the instructions below, by clicking on :
Home -> Create -> Story
Next, we are introduced to the Empty Canvas page where we can do our analysis with the data. In this case, I will drag an excel file with a dummy sports data into this. If you are in need of dummy data sets, you can always download them from this website below :
And… Voila, we are now introduced to a table that consists of the data that we require. Towards the right, we see the information of the dataset like the number of rows and columns. Next, we click on the exploratory view.
I want to compare the Rebound count between the different teams. So, I select Rebounds from ‘Measures’ , and Teams from ‘Dimensions’.
In this exploratory view, we can also change the type of charts, and as we can see from the GIF below, and I select the Marimeko chart.
Here are other useful charts to visualize data : namely the Waterfall chart and the Donut chart !
So, as we’re inching closer to creating our first story, we copy the chart to a new canvas page, where we can insert and edit how the analysis will be viewed to the end user.
There are so many options as we can see, right from inserting an R visualization to inserting any image that we have with us.
I inserted a clock to keep track of my time !
Now, I insert a table and mention the necessary rows, columns and filters. I select the Player’s Name in rows, and filtered to show his Rebounds, Assists and Number of games played.
Last but not the least, let’s create the story by saving it and by giving it a title and a description.
This is just an introductory series of my 4 series blog posts, and I hope it was comprehensive enough to get you started in your data visualization journey !