Name change from SAP Data Warehouse Cloud to SAP Datasphere. Some links may break.

The Datasphere Analytic Model is now on all tenants available. With this wave, you have now the possibility to use instead of an Analytical Dataset (ADS) the new Analytic Model. The Analytic
Model is a kind of cube which allows you to slice and dice your data model. I wrote about the preview access on December,
and now I want to show you some details.

The Analytic Model is the new place to go as a model for the SAP Analytics Cloud (SAC). It allows adding several dimensions and build a nested view of your data. As you see in the screenshot
above, you have now the possibility to make slice and dice like in Analysis for Office. You can easily drag and drop the dimensions to the columns/rows and build the view of the data you need.

As you see in the screenshot, the Bike Sales Orders fact model has two dimensions, the Partner ID and the Product ID. But I have now the possibility to go further down. For example, from the
Partner ID to the Address ID and then to the Country dimension. So I have texts or hierarchies available which are build on the country dimension. This is how it looks like in the preview.

If I now add the Product ID, I can switch to present the hierarchy and this is how it looks:

As you see, the text which is associated to the Product ID dimension is displayed and the hierarchy which is available is also displayed. This is a real benefit for a short data analyze when you
don’t want to create a SAC Dashboard to see the data. Another feature of the Analytic Model is that you have the possibility to create restricted and calculated key figures. You can create basic
calculated key figure but also calculated key figures with exception aggregations.

The calculated key figures can have the following aggregation types:

• SUM
• MIN
• MAX
• COUNT/COUNTNULL/COUNTNULLERO
• AVG/AVERAGENULL/AVERAGENULLZERO
• STD
• FIRST
• LAST

So now the Analytic Model gives you a lot of possibilities which are only provided before by a SAP BEx Query.  Besides the calculated key figures, we have now restricted key figures.

The restricted key figures can be set to a fix value or can be filled with a variable depending on your needs. Which is nice because this input parameter is published to the SAP Analytic Cloud,
so the end user can filter the value they require. Based on the restriction, you can also add an exception aggregation with the same aggregation types the calculated key figure has (see above).

I think the Analytic Model will push the Datasphere to the next level. It is now possible as a data architect to have a preview of the data the department will see in the SAC. So the
understanding is better, and we have now the possibility to create restricted and calculated key figures in the data model and reuse them in the SAC Story. So you don’t have to create them every
time again. We will see how the Analytic Model will develop, but at the moment there are some ideas on the road map. My favorite is here, the support of the Business Layer. What are your thoughts
on the Analytic Model? Let me know in the comments.

Name changed from SAP Data Warehouse Cloud to SAP Datasphere. Some links may break

Someone ask me how you could create a time hierarchy in SAP Datasphere (DSP) to use it in SAP Analytics Cloud (SAC). Because out of the box by just create the time dimension it isn’t working
right now. So here are the steps you have to make.

First we create a new space and start from scratch.

After we created our new space and added our user to this space, we are able to create the time dimensions direclty in SAP Datasphere.

Now we see in the Data Builder of the SAP Datasphere the time dimensions we just created. 

To show you an example I need to upload some example data. We use for this the CSV-File upload functionality of Datasphere. 

My example file here are the sales orders with a date in one column, so we can build our hierarchy.

After I uploaded my files, we can create a new graphical view to associate our time dimension to our sales data.

As you see the view is very simple we just join the sales order header with the details. Now we can assign in the properties of the view element our time dimension.

Now we can select our association target and here we select the time dimension day and click OK.

Now we have to join our view with the time dimension. In my case I use the order date for my hierarchy.

As penultimate step of this view we define our view as an Analytical Dataset and expose it for consumption.  As last step we save and deploy our view to make it available in the SAP
Analytics Cloud.

Now after we have deployed our view we can switch through the application switcher to the SAP Analytics Cloud.

We open via the menu our corresponding space and create a new story there.

Here we have to select our Analytical Dataset.

After we selected our Analytical Dataset, we choose for the demonstration a table to show the hierarchy.

Now we add the Order Date to our table and can select our corresponding hierarchy.

As you see our table shows the time hierarchy.

When you know where the options are, it is not heavy to build a time hierarchy in SAP Datasphere and use it in SAP Analytics Cloud. I hope this will help to get started with Datasphere. If you
have any questions, feel free to ask in the comments.