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SAP Data Intelligence

Score7.7 out of 10

97 Reviews and Ratings

What is SAP Data Intelligence?

SAP Data Intelligence is presented by the vendor as a single solution to innovate with data. It provides data-driven innovation in the cloud, on premise, and through BYOL deployments. It is described by the vendor as the new evolution of the company's data orchestration and management solution running on Kubernetes, released by SAP in 2017 to deal with big data and complex data orchestration working across distributed landscapes and processing engine.

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Categories & Use Cases

Media

Screenshot of Business Glossary
Screenshot of Example of data quality operators
Screenshot of Data profiling fact sheet
Screenshot of SAP Data Intelligence Jupyter lab notebook for machine learning
Screenshot of SAP Data Intelligence data pipeline using Python
Screenshot of SAP Data Intelligence example ata quality dashboard
Screenshot of SAP Data Intelligence connections
Screenshot of SAP Data Intelligence Metadata Explorer
Screenshot of SAP Data Intelligence Example of Table Consumer Pipeline

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Who Buys & Uses SAP Data Intelligence

SAP Data Intelligence Reviews

What users are saying about SAP Data Intelligence.
View all SAP Data Intelligence reviews

Data Intelligence with SAP(Is it worth?)

Kishore Challa
SAP Technical Manager in Information Technology at Syntax (1001-5000 employees)

Use Cases and Deployment Scope

I use SAP Data Intelligence for Sending the Financials & Material inventory data from S/4H to Azure Data lake Should have the knowledge on the terminators and connectors.

Pros

  • Sending the data to Non-SAP Systems
  • Cleansing the data
  • Data Governance

Cons

  • Performance & scalability issues
  • Complexity
  • Documentation & tutorials
  • Limited connectors

Return on Investment

  • Increased efficiency & automation (Positive impact)
  • Data Management(Positive Impact)
  • Complexity in setting up governance frameworks(Negative Impact)
  • Resource-intensive setup and ongoing operational costs(Negative Impact)

Alternatives Considered

SAP Datasphere

Usability

Other Software Used

SAP S/4HANA Cloud, SAP Datasphere

SAP Data Intelligence's analytics have a leg up on the competition.

Incentivized
Dan Rodriguez
Programmer Analyst in Information Technology at SDI Presence (501-1000 employees)

Use Cases and Deployment Scope

In my experience, SAP Data Intelligence simplifies the process of bolstering data-sharing, pipelineing, and governance in a networked environment. I think the supply chain and logistics industries may benefit form SAP Data Intelligence. It has enormous potential for waste minimization.

Pros

  • Lessen the total processing time.
  • Compatible with a wide variety of add-ons.

Cons

  • Failures in a Kubernetes cluster might be difficult to diagnose.
  • I think it's easy for mistakes to be made during installation.

Return on Investment

  • Improvements in efficiency and new ideas.
  • Complex business processes are simple to analyze and forecast.

Usability

Other Software Used

SAP Access Control

SAP Data Intelligence Feedback

Incentivized
Srini Ganapathiraju
Engineering Manager in Finance and Accounting at INGKA Services LLP (10,001+ employees)

Use Cases and Deployment Scope

This product is mainly used for Event processing and requires additional capabilities on how this product helps on Event Mesh and Data Mesh solutions, especially how this is useful to enable Data Product.

Pros

  • Event Processing

Cons

  • Standardization of transformation solution

Return on Investment

  • Licensing cost is too much which does not make sense from ROI

Alternatives Considered

StreamSets DataOps Platform

Usability

SAP Data Intelligence: family of SAP for the help

Incentivized
Sabit Shaiholla
Head Research Assistant in Engineering at Nazarbayev University JSC (1001-5000 employees)

Use Cases and Deployment Scope

This SAP's Data Intelligence software tool is used for the implementation of for data integration (based on ETL and ELT processes) with defined scope of functionalities and capabilities provided. Moreover, it provides great integration with other SAP products such as SAP 4HANA. We utilize it in conjunction with AWS and Microsoft Azure tools.

Pros

  • Good integration and data migration functionalities (from one DB cluster to another)
  • provision and support of different level of data access (tabular format level, ETL layer level, ODP level)
  • Reasonable pricing (pay-as-you-use strategy, without overhead cost implemented)

Cons

  • High entry level of usage - for some users like me it is hard to get things performed without referring to the tech support and their documentation
  • the management and control of the source code imposes the difficulties in terms of ease of usage - with complex projects this issue is critical and becomes a bottleneck for the further development processes implemented
  • as easy it is to manipulate and perform operations on tabular data, as hard it is to work with non-relational database entities such as semi-structured documents and files

Return on Investment

  • This tool has provided great functionality on migrating DB cluster, therefore having directly positive impact on ROI by reducing the operating costs with the support of Oracle DB
  • It has provided decreased time-to-market delivery, as we have expected to finish the whole project in 6 months instead of 3. This had a enormous impact on the overall performance of the project, with great advantage in terms of ROI.
  • With the decrease of operating costs, we have optimized the overall budget devoted to the support of our DB clusters, thereby improving the cost budgeting
  • Overall, very reasonable pricing strategy provided (pay-as-you-go)

Alternatives Considered

StreamSets DataOps Platform and Azure Data Factory

Usability

Other Software Used

Azure Data Factory, Azure Machine Learning, Azure Managed Grafana, Azure Migrate

Business Self-Service Analytics for Data Discovery and Verification

Incentivized
Uvaraj Shanmugam
Sr. Business Intelligence Architect in Information Technology at Becton Dickinson and Company (10,001+ employees)

Use Cases and Deployment Scope

The main purpose of the usage of SAP DI in our platform is to have the Lineage end-to-end from Reporting to Source origins, building Data Catalog for users to enable self-service analytics for Exploration and Discovery, Data Quality assessments and take effective decisions.

Pros

  • Lineage at the object level
  • Pipeline build for Data Integration
  • Data Catalog for self-service analytics

Cons

  • Lineage at attribute(column) level to help Impact Assessment (just like SAP Information Steward)
  • Lineage on non-SAP sources could be a game changer, most of the companies fail in this area which will be an eye opener for customers like us.
  • on Data Integration space, Provide Detailed Road Map on SAP DI compared to SAP Data Services(aka BODS) and SAP SDI

Return on Investment

  • we are very new and i think it will make a significant capability in the Data Catalog and Lineage space in our Org to start with.

Usability