Why Should You Use The SAP ETL Tool

SAP is an acronym for System Applications and Products. This Enterprise Resource Planning Software is very useful in organizations in the areas of sales, finance, inventory, production, HR, and more.

ETL is the short form for Extract, Transform, and Load. This tool is critical for extracting data from a source database, transforming it to the structure supported by the target database, and finally, exporting it to the intended database.

The goal of the SAP ETL is to move data between SAP environments and integrate various systems and data formats into each other. Checks can also be done by it to verify whether the value of a name has been allotted and to run checks to clean the data. The most critical feature of SAP ETL is that data can be extracted even from outside an application.

The SAP ETL replication is used by the SAP Data Services to move data from non-SAP or SAP sources to the target HANA database. Another equally efficient ETL tool for extracting, transforming, and loading data from a source to the target database is the BODS system that enables reading and analyzing data at the Application layer. Before doing so, though, the data flows in the Data Services need to be named, replication activity has to be scheduled, and the target system has to be defined in the data store within the Data Services Designer.

Features of the SAP ETL Tool

The SAP ETL has several cutting-edge and technologically advanced features.

• When connected to the Data Extractors or CDS views, the SAP ETL tool automatically extracts data through the OData services for extracting both first run and incremental data or deltas.

• Wherever access to the primary database is permitted, the SAP ETL tool carries out log-based CDC (Change Data Capture) from the database through transaction logs. It also helps to extract data from Pool and Cluster tables to the SAP data lake or data warehouse

• By automatically merging deltas with the initial data, SAP ETL is always updated in real-time on the SAP data lake running on Snowflake, Redshift, Amazon S3, and Azure Synapse.

• For SAP ETL activities like extraction, merging, masking, or type 2 history, coding is not required as is external integration with third-party tools like Apache Hudi.

• Automated SCD Type 2 history of the data ensures that the history of every transaction is preserved on the SAP data warehouse or data lake.

• Best practices and high integration performance into Snowflake, Redshift, S3, Azure Synapse, Azure SQL DB, and SQL Server are provided by SAP ETL thus making sure that the data in the SAP Data Lake or SAP Data Warehouse is always analytics-ready.

• Automatic integration with Amazon Athena and Glue Data Catalog is assured by an SAP Data Lake on AWS at the API level.

These are some of the key benefits of the SAP ETL tool.