What is Data Warehouse Cloud?
The latest enhancement to the SAP Business Intelligence offering, SAP Data Ware Cloud (DWC) is a cloud-based information stockroom option developed by SAP. It is easy to incorporate data (from either an SAP system or an outside one), rework, finish this content with various other sources, to finally provide it in a summarized form in a dashboard.
It is a tool that allows for managing end-to-end data circulation. To accomplish that, we will examine 3 levels:
- Data integration
- Data modeling
- Analytical layer
The first SAP Data Warehouse Cloud accessibilities were granted to SAP companions in August. As a data fanatic, I wished to share my initial experience with this new SAP Cloud product (beta release) with you.
In the following post, I will explain in 4 easy steps how to create a dashboard based on data from a third-party system, with an “OData” data connection.
Required for the purpose of this tutorial
To follow this tutorial, you should have access to an SAP Data Warehouse Cloud environment.
If you do not have an SAP Data Warehouse Cloud instance, you can access a 30-day trial environment by clicking here.
( After receiving a verification email, you need to obtain a subsequent e-mail to access your environment within 5 mins.).
1) Create your management room
Let’s start by creating a management space where you can store your data.
In the left-side drop-down menu (1 ), click “Space Management,” and after that on “+” to create a new space(2 ):
Name your management space to your preference, then click on “Create.”
You just created a new area.
You can manage allocated space, individuals that can access it, or connection leading to it. Later, I will discuss how you can include users or connections.
Let’s move on to the next step, which will allow that space to store data.
2) Configure the “OData” connection.
In the drop-down menu, click on “Connections” (1 ), and click on “+” (2) to include a new connection.
In our example, we will choose an “OData” type of connection.
Enter a name for this connection and the URL on which you can access your data.
If you have an OData service that permits you to deal with your company’s data, you can indicate it here.
I used a public OData provider that you can use by getting to the following address: https://services.odata.org/V3/Northwind/Northwind.svc/.
Then, enter the customer name and password to access your OData service (if no verification is called for, you will still have to complete the “Customer Call” and “Password” fields to access the confirmation button).
Once those fields are filled, click “Confirm.”
Once the connection is created, you need to check that it is operational by clicking the “Status” button of the recently included line. If everything works, a message indicating that the connection is valid will appear.
You need to appoint this new connection to the management space before you can use it. Go to your workspace(1 ), then switch to the “Display space” mode.
Add users that will need access to it.
Finally, click on the “+” button to add a connection(4)and choose the one formerly created.
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4) Modeling your data
When the connection is established, you will have the ability to model your data.
In the left-side drop-down menu, click “Data Builder,” and select the previously configured working space.
Once in that working space, create a new graphical view to model your data.
When in the modeling space of the graphical view, select the “Resources” tab; in the connection folder, click on the one you just created.
You will have the ability to see all the entities that have been uploaded from the OData flow.
To start, drag/drop an entity on “Orders” (1 ). The system will prompt you to import the table so it can deploy the data, and accept it.
A second box, called “Output” (2 ), is automatically created. It appears to be the last step of a graphical view. It will allow us to preview the output data.
It is now possible to model the data as we wish thanks to the tool’s numerous functionalities.
In our example, I will sign up with data from various entities amongst themselves, below, and order-related data to those of the employees.
The drag/drop function of one entity onto another allows one to conveniently join them and quickly get the finished model.
To explain this example’s modeling, 5 important functionalities should be highlighted:
- A filter can be applied to the data exiting an entity to then be signed up with;
- We can, at any time throughout the data modeling, see which data is being published;
- Formulas can be applied after each action (uploading of data, connections, etc.). For instance, we will create a column based on 2 metrics of the previous entity;
- It is possible to pick the Join Type linking entities, there are six possible choices: inner, outer-right, outer-left, crossed, complete, natural;
- The projection operates after each joint to select the data to upload on each side of the resources of data comprised in that joint.
- At the last stage, after applying all the preferred settings to ensure that all data is properly submitted, it is possible to preview the data.
To access that data in the following action, the graphical view must be set to “Fact” to differentiate the measurements of the dimensions.
You must then sort the measurements of the dimensions, and lastly, save and deploy the graphical view.
4) Exposing Data
Let’s move on to the Data Visualization step.
In the drop-down menu, picked “Story Builder” and then select a workspace;
Click “Create Story” to develop a new presentation.
The system will prompt you to select a data source.
In the drop-down menu, choose the graphical view previously created
Once the data source is added, start creating data graphs such as the ones we can create with SAP Analytics Cloud.
Create charts by selecting dimensions as the analysis’s axis, and then the metrics you want to explore.
Create as many charts as you need to make a pertinent analysis of your indicators.
Once your dashboard is completed, it is ready to be shared with the stakeholders, during daily, weekly, or monthly meetings.
Conclusion
In this article, we understood how easily you can upload data from an OData data resource to an SAP Data Warehouse Cloud. We could also conveniently create this circulation by importing data from a cloud-based or on-premise SAP S/4HANA system, an SAP BW/4 HANA, or SAP BW using the two various other recommended connection types “SAP ABAP” or “SAP HANA”.
The combination of the SAP Analytics Cloud presentation layer in SAP Data Warehouse Cloud allows gaining access to a number of the functionalities of a product tested and approved for the creation of dashboards.
The modeling part is complete and gives all the functionalities required to filter data, add solutions, create connections, or visualize at any stage.
Ultimately, the most important innovation for this SAP Cloud tool is its ability to save a large volume of data online. All this without risking the security and the confidentiality of your data, thanks to the expertise SAP has acquired in that field over the years.
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Closing Notes
Now, if you’re willing to learn from the best, then you’re in the right place. At ZaranTech, we offer self-paced online training in SAP Data Warehouse Cloud conducted by experienced industry experts. Browse through our course page for details.
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