Capturing Data with The SAP BW Extractor

The SAP BW Extractor is a program for users for capturing and preparing data in SAP ERP. This is done through an extract structure that is transferable to the BW (Business Warehouse). This program can be run from a standardized Data Source or customized as per specific needs. In both cases, a full process load of various types or a delta load process has to be defined. The SAP Business Warehouse can remotely access the various aspects of the SAP BW Extractor.


The question now is whether all data will be lost if the SAP BW Extractor is moved to S/4HANA or other SAP BW Extractors that are compatible with S/4HANA.

The point is that only transactional and operational activities can be done and not analytics by the SAP ECC system. Hence the SAP BW Extractor is required to extract data from the SAP ECC system to an SAP BW system to analyze ECC data. After linking the SAP BW Extractor to a BW system, the latter can perform analytical activities by connecting to the Business Intelligence system.

Extraction of data can be started with the multiple application-specific extractors by the SAP BW Extractor. These are then delivered along with the BI Content in the BW after being hard-coded for the Data Source.

SAP BW Extractor enables three types of data extraction.

1.     Content Extraction: It is used to extract BW content, FI, HR, CO, SAP CRM, and LO cockpit.

2.     Customer-Generated Extraction: Here, SAP BW Extractor is used for LIS, FI-SL, and CO-PA.

3.     Generic Extraction: This is based on DB View, Infoset, and Function Modules.

Businesses use anyone as per their specific requirements. 

Comments

Post a Comment

Popular posts from this blog

The Unique Architecture of the SAP HANA Data Lake

Image
In April 2020, SAP launched the HANA Data Lake that added more power to the existing cloud-based business ecosystem. Users benefitted from a cost-effective storage system from the package that consisted of a native storage extension and a relational SAP data lake. From the start, this data lake was considered to be as feature-rich as the existing players like Microsoft Azure and Amazon S3.  What makes SAP data lake stand out among its competitors is its unique architecture. Organizations have the option of storing data that is frequently used and regularly accessed in one layer while moving other not-so-critical data in low-cost storage layers of SAP HANA. Visualize the SAP data lake as a pyramid that has three layers. The top of the pyramid houses the most important data of an organization that is used in the regular course of business. Hence the cost of storing this data is the highest as it is frequently accessed for analytics or reporting. In the second layer of the ...
Read more

The Unique Architecture of the SAP Data Lake

Image
SAP launched HANA Data Lake in April 2020, intending to provide users with an advanced as well as a very cost-effective data storage repository. The complete package consists of a native storage extension and an  SAP Data Lake   that is standard across all models and versions. The architecture of the SAP Data Lake is unique and stands out from other forms of data lakes. Businesses have the option to store data that is frequently used and accessed (hot data) segregated from data that is not used much (warm data) in the Native Storage Extension (NSE) of SAP HANA. The SAP Data Lake may be visualized as a pyramid with three distinct layers. On the top part of the pyramid is space offered to businesses to store the data which is critical for daily operations and has to be accessed daily. Since this data has very high demand, the storing cost too is the highest among all the three segments. The middle layer of the pyramid is for organizations to store data that is no...
Read more

Everything you need to know about Extract, Transform and Load (ETL) tools

Image
As a central repository that holds all the bid data from various different sources, a data lake is the vast, richest pool of raw data, the purpose of which is undefined. Data from this lake is then put to use for analytics and machine learning by organizations. A data lake is used for storing both relational and non-relational data from devices, apps, and users. Different types of analytics, such as machine learning, big data analytics, textual search, SQL queries, and real-time analytics can be derived from a data lake. It has both curated and non-curated data. An SAP data lake is easy to set up and can ingest data from on-premise or from a cloud warehouse. According to a survey, 90% of businesses believe that big data initiatives help them determine future success. A data lake allows data engineers, data scientists, and business analysts to access information using the tools and applications of their choice. There’s a lot of value in a data lake for businesses, the ability to harnes...
Read more