This paper provides an insight into Best Practices for SAP to Hadoop data Integration to verify the success and completeness of data Integration, thereby assuring the continuity of operational performance after the completion of data Integration activities.

1. SAP and Hadoop
Data Integration
Applications
S/4HANA on-premise edition
Whitepaper
www.chainsys.com

2. Objective
This paper provides an insight into Best Practices for SAP to Hadoop data Integration
to verify the success and completeness of data Integration, thereby assuring the
continuity of operational performance after the completion of data Integration activities.
Meena R
Business Analyst
Chain-Sys Corporation
Passionate about software technology, Meena recently
upgraded her skillset to become a certified Data scientist,
after 6+ years with multinationals in the IT field. As
business analyst at ChainSys, she's excited to lend her
expertise towards improving product usability, and
innovating business processes to improve
customer satisfaction.

3. Data Integration Process Steps
Steps to configure:
Create a connection to the SAP instance.
Create a connection to the Hadoop based systems like Impala or Hive.
Create a new Data object to extract data from the SAP.
Create a new Loader to load the data into the Hadoop system.
Create a new DataFlow to map the Data Object and Loader.
Schedule/Publish the DataFlow to integrate the data from SAP to Hadoop.
dataZap is a Chainsys Platform for Data Integration, where cloud to cloud integration, on-premise to
cloud and cloud to on-premise Integration are accomplished by quick drag and drop development
with no programming. You can add/manage business rules and transformation logic using the
intuitive wizard based GUI of dataZap, making it simple to manage the enterprise-wide
integration strategy.
For example, consider a case of a Global Organization, where the customers are created in various
ERP applications like SAP, E-Business Suite etc. The data is distributed over multiple source systems.
The data tends to become redundant with a lot of duplicate entries. In order to overcome these
complexities and streamline the Customer data, it can be integrated into a Data Warehouse for
analyzing and cleansing and migrate the cleansed data to any ERP Cloud/On-Premise platform.
EXPECTATIONS
BUSINESS
SAP and Hadoop
Data Integration
™

4. Connection
Ensure that the respective SAP source connection is available. If not, create a new connection.
Verifying the Source Connection:
Ensure that the respective Impala target connection is available. If not, create a new connection.
Verifying the Target Connection:

5. Data Object:
Create a new Data Object using the SAP connection and enter the BAPI details to extract data.
Loader:
Create a new Loader using the Impala connection and enter the table details to load data.
™

6. The mapper has the features "Exact Match" and "Pattern Match" to map the column easily.
DataFlow:
Create a Dataflow to map the source and target columns to integrate the data.
Select the source as Data Object and pick the newly created Data Object.
Select the target as Loader and pick the newly created Loader.
Create the mapping between the source and target columns.
You can execute the Dataflow manually and the results would look like the following,
™

7. Conclusion:
Thus the data is integrated from SAP to Hadoop(Impala) successfully with no coding just by drag and drop.
About ChainSys
Supported Endpoints
For Case studies, references, or a no obligation trial & proof of concept,
visit us at chainsys.com/
Chain-Sys is a trusted innovator in the API Economy , ChainSys is a leader in the data migration,
integration, data maintenance, MDM, data quality, data cataloging, machine learning, AI, analytics,
visualizations, audits, compliance and RPA based autonomous testing & low-code web/
mobile application building areas. ChainSys has successfully deployed its SmartBOTS in a Platform
in several Fortune companies worldwide, and continues to grow and innovate rapidly. Headquartered
in Lansing, MI, and spread across 5 continents, ChainSys prides itself on its Product, Process & People
which constantly push the envelope on innovation & creativity
For Batch Integration, schedule the Dataflow.
For real-time integration, publish the Dataflow as a REST or SOAP API.

8. Supported Endpoints ( Partial )
Oracle Sales Cloud, Oracle Marketing Cloud, Oracle Engagement Cloud,
Oracle CRM On Demand, SAP C/4HANA, SAP S/4HANA, SAP BW,
SAP Concur, SAP SuccessFactors, Salesforce, Microsoft Dynamics 365,
Workday, Infor Cloud, Procore, Planview Enterprise One
Windchill PTC, Orale Agile PLM, Oracle PLM Cloud, Teamcenter, SAP PLM,
SAP Hybris, SAP C/4HANA, Enovia, Proficy, Honeywell OptiVision,
Salesforce Sales, Salesforce Marketing, Salesforce CPQ, Salesforce Service,
Oracle Engagement Cloud, Oracle Sales Cloud, Oracle CPQ Cloud,
Oracle Service Cloud, Oracle Marketing Cloud, Microsoft Dynamics CRM
Oracle HCM Cloud, SAP SuccessFactors, Workday, ICON, SAP APO and IBP,
Oracle Taleo, Oracle Demantra, Oracle ASCP, Steelwedge
Oracle Primavera, Oracle Unifier, SAP PM, Procore, Ecosys,
Oracle EAM Cloud, Oracle Maintenance Cloud, JD Edwards EAM, IBM Maximo
OneDrive, Box, SharePoint, File Transfer Protocol (FTP), Oracle Webcenter,
Amazon S3
HIVE, Apache Impala, Apache Hbase, Snowflake, mongoDB, Elasticsearch,
SAP HANA, Hadoop, Teradata, Oracle Database, Redshift, BigQuery
mangoDB, Solr, CouchDB, Elasticsearch
PostgreSQL, Oracle Database, SAP HANA, SYBASE, DB2, SQL Server,
MySQL, memsql
IBM MQ, Active MQ
Java, .Net, Oracle PaaS, Force.com, IBM, ChainSys Platform
Oracle E-Business Suite, Oracle ERP Cloud, Oracle JD Edwards,
Oracle PeopleSoft, SAP S/4HANA, SAP ECC, IBM Maximo, Workday,
Microsoft Dynamics, Microsoft Dynamics GP, Microsoft Dynamics Nav,
Microsoft Dynamics Ax, Smart ERP, Infor, BaaN, Mapics, BPICS
Cloud
Applications
PLM, MES &
CRM
HCM & Supply
Chain Planning
Project Management
& EAM
Enterprise Storage
Systems
Big Data
No SQL Databases
Databases
Message Broker
Development
Platform
Enterprise
Applications

9. One Platform for your
Data Management needs
End to End
www.chainsys.com
Data Migration
Data Reconciliation
Data Integaration
Data Quality Management
Data Governance
Analytical MDM
Data Analytics
Data Catalog
Data Security & Compliance