SAP ETL
André Magalhães Manager

SAP Data Services and SAP Datasphere: From on-premise ETL to cloud-first ELT

In this competitive world where data is the new "gold", the winners are those who from data can extract valuable information and consequently knowledge through the most diverse methods such as AI, Machine Learning or Data Science.

ETL and ELT processes: centralize data on-premise and in the cloud

It is on this journey that, around 40 years ago, the ETL (Extract, Transform and Load) processes emerged that are still in force today and that aim to simplistically aggregate all data in a  consistent and uniform way in a centralized location (Data Warehouse).
 

ELT (Extract, Load and Transform) arises from current needs and is usually associated with new Cloud environments. This exchange of initials, although it seems only a lexicon exchange, introduces a new paradigm of data loading. ETL handles the transformation phase on a processing server before placing the data in the Data Warehouse. On the other hand, from the ELT point of view , the data is loaded and transformed within the Data Warehouse itself.
 

SAP Datasphere


SAP's solution for data integration, oriented to the on-premises world, is SAP Data Services. Mature solution, very oriented to the traditional ETL process and  corporate reporting with the Business Objects (BO) offer.

In line with its cloud-first strategy, SAP has been offering SAP Datasphere, originally named SAP Datawarehouse Cloud, as a new solution fully implemented in the Cloud within SAP BTP, which in addition to data integration offers reporting and dashboards through SAP Analytics Cloud within the same Cloud platform.

SAP Trend: Future and Innovation with SAP Datasphere

Excluding hybrid scenarios, which exist and with great success (e.g.: Data Services + BO Universes but using SAP Analytics Cloud to consume these), the SAP strategy and the trend of global adoption of Cloud environments for reasons that are more than debated and justified are driving all new customers to SAP Datasphere with SAP Analytics Cloud, and it is in this combination that innovation happens very regularly with new features released quite regularly.

AP Datasphere is more suitable for companies that have large volumes of data

The choice between ETL in SAP Data Services or ELT in SAP Datasphere depends fundamentally on the available infrastructure (Cloud or On-Premises) and the company's medium-long term vision.
 

SAP Data Services is ideal for organizations that have an adequate infrastructure, usually with SAP Business Objects also present (for reporting capabilities) and maintained in-house. A stable solution albeit with regular updates for the maintenance of support (SAP Data Services 2025 on the way).

On the other hand, SAP Datasphere is more suitable for companies that have large volumes of data, especially in Big Data or Cloud environments. Its Cloud architecture, where data can be quickly uploaded, transformed and presented, as well as the current innovation, with a more modern and appealing 'look & feel' are its strengths. A solution for the future, increasingly solidified and still with a great margin for progression.