SAP Data Services

Score8.6 out of 10

36 Reviews and Ratings

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What is SAP Data Services?

SAP Data Services is an offering from SAP to improve data quality.

Categories & Use Cases

Data Quality

Master data management (MDM) integration
Quality of integration with MDM systems
Category average: 8.6
Data element standardization
Parsing and standardization of data elements according to predefined rules
Category average: 8.3
Address verification
Data format checking and valid address checking
Category average: 8.6

Data profiling
Ability to find anomalies and hidden relationships between data elements
Category average: 8.3
Data source connectivity
Ease of connection to multiple data sources
Category average: 8.3
Match and merge
Ability to identify potential matches and then merge
Category average: 8.2

Maricriz Nolan

Cyber Security Engineer Sr Staff at Lockheed Martin (10,001+ employees employees)

Use Cases and Deployment Scope

ETL to load data from both SAP and non-SAP systems to HANA as well as vice versa. SAP has been able to provide drivers and connectors so that data can be stored centrally for reporting and analytics purposes.

Pros

ETL tool to load data from SAP and non-SAP systems into HANA.
Have local scheduling as well as being able to be interfaced to other scheduling tools.
The Data Services designer is easy to use by developers to create their workloads.

Cons

Needs improvement on error descriptions. Some are too vague and require additional labor.

Return on Investment

Application has been reliable with high priority data loads.

Vivek Yalla

Sap basis architect in Information Technology at Cognitus (51-200 employees employees)

Use Cases and Deployment Scope

Maximize the value of all your organization’s structured and unstructured data with exceptional functionalities for data integration, quality, and cleansing.

Pros

cleansing
quality
data integration

Cons

Change Data Capture
Data Services Workbench
Cloud Platform Integration – Data Service (CPI-DS)

Return on Investment

Performs well in orchestrating disjointed data assets into actionable business insights and gives the organization holistic data management.
Transform, cleanse, match, and consolidate data by understanding the impact of quality problems on all downstream systems and applications.
Unlock meaning from unstructured text data to increase business insights by supporting a wide variety of SAP and non- SAP information sources.
Integrate, connect, and process all structured or unstructured critical data from SAP or non-SAP sources, within Big Data or enterprise solutions (on-premise or cloud).

Other Software Used

Oracle Analytics Cloud Day by Day, Azure Data Factory, Google Data Studio

Kevin Clemons

BI Manager in Information Technology at Utegration (201-500 employees employees)

Pros

Repetition of the same extract or transform for different needs. We can use variables to use the same ETL job for different types of aggregations.
Reliability of the jobs through the use of audit features. We can add audit gates to check for table counts and automatically send out notifications and alerts.

Cons

Heavy processing is required to run the standard transformations. We get around this by creating custom SQL transforms, but lose insight when we take this approach.
Delta loading is possible but sometimes difficult. It sometimes requires customization that creates maintenance issues.

Return on Investment

As an enabler of SAP HANA, it's required. So, it's a positive ROI when SAP HANA is factored into the equation.
We use SAP Data Services for migration into SAP migrations, and this creates a positive ROI for our implementations for new or existing clients.

Alternatives Considered

Informatica Application ILM

Other Software Used

SAP BusinessObjects Business Intelligence (BI) Platform, Tableau Server, Microsoft Power BI, SAP HANA

Martin Lopez View profile

Gerente de Consultoría in Product Management at SEIDOR Analytics (201-500 employees employees)

Pros

The ETL construction process its very easy. Its ease of use and the fact that the design of the processes is completely graphic makes its learning process very fast.
Support on ETL Migration.
Data Quality Projects.
Metadata Administration.
Its connectivity capabilities with different database platforms, applications and cloud systems are excellent and has been growing with the evolution of the different versions.

Cons

New connectivity options for cloud solutions must be added.
Avoid dependency from flash in Information Steward scorecard.
More connectivity options for hadoop distributions.

Return on Investment

Very positive impact in jobs maintenance since support auto-documentation.
Great impact on learning curve.
Great results in our Data Quality Projects.

Alternatives Considered

SQL Server Integration Services

Kiran Bhat View profile

Application Development Manager/Solutions Architect in Information Technology at Dawn Food Products (1001-5000 employees employees)

Pros

Integration with SAP ERP/ECC works really well.
A lot of flexibility in data creation, with different types of communication capabilities like BAPIs, IDocs, and Batch input.
Reliable and consistent results and easily enforceable data templates.

Cons

Initial setup of rules requires more technical expertise than master data management teams are typically used to.

Return on Investment

DS has had a very positive impact by reducing deployment times for SAP and has provided ability to deploy multiple sites at the same time.
Ongoing master data creation/migration benefits significantly from DS, and it's easy to stand up a new business unit.
Data accuracy improved and manual inspections are minimal.

Other Software Used

SAP ERP, OnBase by Hyland, Dolphin ImagingPlus

Informatica Cloud Data Quality

IBM InfoSphere Information Analyzer, compo

Oracle Enterprise Data Quality

SAP Data Services

What is SAP Data Services?

Categories & Use Cases

Key Features

Top Performing Features

Master data management (MDM) integration

Data element standardization

Address verification

Areas for Improvement

Data profiling

Data source connectivity

Match and merge

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