One of the primary reasons businesses invest in robust solutions such as the SAP HANA Cloud is its data management capabilities. Data is the new gold, and every business, irrespective of its scale or industry, must leverage the potential of data to drive better and more effective results.
SAP HANA cloud platform comes with varied data management features and functionalities to help organizations leverage the full potential of data. This enables organizations to achieve optimum analytical capabilities that are further leveraged to drive better and more effective business decisions.
However, in order to be able to make the most of these features and functionalities, one has to be aware of all the data management techniques and concepts in the SAP HANA cloud platform. Therefore, let’s check out some of these techniques and concepts.
The Scale Pyramid or Data Storage
The idea behind the data pyramid has been around for quite some time now, and businesses have time and again used this to their advantage. The idea behind the data pyramid is not as complex as one might imagine. It is all about placing your data on different tiers based on the required competencies, such as performance or access. The in-memory tier is dedicated to the data used frequently or even requires essential latency.
There are basically two primary aspects associated with data and pyramids. The first is data tiering, where data is moved between tiers based on a predefined set of rules. The second is data placement which is a process where one places data at a specific time during the process 0of data acquisition.
The distinction between both processes is not very complex. In data tiering, there are certain rules for data within the pyramid to promote or demote the data while still in the pyramid. In the case of data placement, the data is acquired from external sources and then placed on the specific and best-suited tier within the pyramid.
Different tiers within the Data Pyramid
As you already know by now, there are different tiers within the data pyramid. Hence the data pyramid is generally made of varied components from the SAP HANA cloud platform. These components include:
- SAP HANA Database: This component is responsible for providing the SAP HANA in-memory and the native storage extension capabilities of the platform.
- Data Lake IQ: The data lake IQ provides the high performant SQL analysis of more significant storage volumes. The SQL analysis is based on the SAP IQ on-premise, which many even refer to as SAP HANA Cloud data lake IQ.
- Data Lake Files: This is the component that provides one with access to structured, semi-structured, and even unstructured data stored as files within the data lake. The data lake files also come with file containers that store data much more effectively.
Furthermore, it is worth mentioning that these capabilities and concepts, as discussed here, are suitable for both cloud and on-premise SAP S/4 HANA solutions.
There are many simple methods that can be used to acquire data into varied tiers of the data pyramid. Therefore, a user can opt for the best-suited data replication or acquisition method depending on the target.
Two different approaches are used to move data from one tier to the other. One can use the SQL competencies of every tier and enhance it further with SQL on files. Other than that, one can always use the service-based approach, which is a hypothetical approach as no such service is offered.
However, you always have the option to implement such services by using different yet relevant APIs offered by every individual layer. In case this does not work, one can always go for different data management solutions such as the SAP Data Intelligence.
The sole reason behind collecting data is to consume it. When we look at data from the context of the data pyramid, it is evident that data can be consumed from any tier by leveraging different methods. These methods include direct consumption from any of the tiers and consumption through the SAP HANA tier by leveraging the federation to other tiers.
This further means that you can reach the tier independently, but this will only give you a partial view of the data. Therefore, it would be best if you could consume the complete data set from a single place. This is where the federation will come in handy ad federation data in HANA data lake files to HANA data lake IQ by using SQL on Files. Other than that, the federate data in HANA data lake IQ to transform the same to HANA cloud files.
How to alter the visibility of data?
The union node pruning approach is ideally suited when it comes to performance. However, that does not address the data consistency aspect, which is of the utmost importance in SAP cloud integration platforms. This means when moving data from one tier to the other, there can often be issues with data duplication. Therefore, experts recommend enhancing the entire concept of pruning to ensure that only a single data tier is queried for any specific set of data. This is the best way to address the complications that arise with data consistency in SAP cloud platforms.
Data management is an important aspect of your SAP solution, and using it to your advantage can yield many benefits for your organization. However, data management can often turn out to be a complex aspect, so leveraging the aforementioned information can be very helpful in such cases.
Therefore, remember these important aspects that SAP HANA Cloud platform offers seamless and comprehensive implementation of the data pyramid concept. Also, there are numerous competencies that can be used to facilitate interaction and movement between different data tiers.
Lastly, the SAP HANA Cloud’s data federation can provide you with transparent and comprehensive access to data throughout the pyramid. Therefore, get your organization teamed with some of the best SAP implementation companies and leverage the full potential of data management in the SAP HANA cloud platform.