In this blog post, I would like to share with you my experience and insights on SAP’s new Data Warehouse Cloud. In my opinion, the best way to learn about a product is to dive into yourself and play around with it to get the feel, explore the features and capabilities before building something big.
In this series of blog posts that are yet to come, I will start from scratch and start from the basic level to the advanced level of the data warehouse with SAP Data warehouse cloud.
If you would like to get more information about this new SAP Data Warehouse solution you can certainly see very valuable information in the links below:
There were also hands-on workshops taking place which have recently been concluded. However, you can still review the sessions and exercises that were covered during these workshops. Register your self with the below link and get access to all the latest information about SAP Data Warehouse.
With that said let’s get to business!!!.
How to import Data from Flat File to Data Warehouse Cloud (DWC)
Log on to your Data Warehouse Tenant > Data Builder > Locate to your workspace.
To find out more about what are SPACES. See this Link.
Here you will see existing work created by others or by yourself. To create a new exercise where you want to load data from a flat-file into Data Warehouse Tenant click on Import CSV File.
Browse your flat file from Desktop and import.
Once the file is imported you are prompted into this below screen which gives you the flexibility to make some initial changes or use the appropriate delimiters according to your flat-file format. I will leave it as Auto-Detect and the tool will detect automatically which delimiter suits best.
Once that is adjusted, you click UPLOAD.
You will now see a preview of the dataset.
You will notice the tool automatically has detected the data types and you are no longer required to manually change any fields according to the type of data your file holds (i.e. which columns are detected as Attribute or Measure). It will also highlight the number of Rows & Columns uploaded.
The following data wrangling features are available:
- Change the columns Names according to your needs
- Split any columns
- Transform any Column with attributes such as (Concatenate, Split, Extract, Replace, Change, Filter).
- Duplicate any column or Delete any Column
- Set or Remove any column as a KEY
Once you have made all the required changes to your dataset you can go ahead and DEPLOY.
However, before it is fully deployed you will be required to provide a meaningful name for your local table that you are about to create. The following would appear.
After a successful DEPLOYMENT, you should then be able to see a local table being created in your repository which holds the dataset from the flat file you uploaded, and you can view this in the “Data Builder Section”.
Note: When you save your table, it is saved in the local repository. When you deploy the table, a view is created in the SAP HANA platform. After creating a table or a view, you can save your work. By doing this, the metadata is saved in your local repository. This means you can always go back and adjust your table if needed. If you are ready and want to work with your data, for example, to build a story, later on, you need to deploy your tables and views. By doing this, the artifacts are saved in the database and are available to other users in your space. If you don’t deploy your tables, they won’t be visible to others to work with.
Even though it is deployed you can still make any further changes you might need or have forgotten with the below-highlighted options.
Specify any description you want to and give it a business name and purpose. Etc.
At this stage you would be able to use this table in any other views you would want.
You can also double click on the table which will bring you to the table properties page.
- You can review the technical and business names given to the table.
- You can enter any description about the data or the tables etc
- You can further add any admin details such as (responsible Team, Contact person, etc).
- Finally, you will also be able to see the details of the columns with their technical names and their data types.
- Any changes to the column’s names for example at the start you would see them being replicated in this screen as well
If you want to double-check and see if your data is ok you can do a data preview as well.
You can now save your table if no further changes are required BUT do not forget to deploy it.
Great!! We are now done with loading data from flat-files into your SAP Data Warehouse Cloud. In the next blog, we will continue from here with the same dataset/local table and create a story/dashboard with SAC (SAP Analytics Cloud) which is embedded already into your SAP Data Warehouse Cloud.
If you have any questions about what I have done in this blog post please feel free to ask them below in the comment section. If you have any questions regarding SAP Data Warehouse Cloud in general, please post them into our Q&A section in the link below: