#1 most frequent
United States of America
45.9%105 installations of 229
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.
Categories & Use Cases
Media
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Screenshot of Business Glossary
Who Buys & Uses SAP Data Intelligence
#2 most frequent
Germany
10.5%24 installations of 229
#3 most frequent
India
7.0%16 installations of 229
Data Intelligence with SAP(Is it worth?)
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
A great product from SAP for your data orchestration and data management needs
Use Cases and Deployment Scope
SAP Data Intelligence is helping us solve the following business problems.
1. Handle huge volumes of data coming from a variety of sources.
2. Orchestrate data pipelines with optimum governance around them
3. Helping in data management activities with its strong feature set on data profiling, data cataloging, etc.
4. Helping us prepare data for our AI/ML processes
1. Handle huge volumes of data coming from a variety of sources.
2. Orchestrate data pipelines with optimum governance around them
3. Helping in data management activities with its strong feature set on data profiling, data cataloging, etc.
4. Helping us prepare data for our AI/ML processes
Pros
- Data pipeline orchestration capabilities
- Data governance
- Scalability
Cons
- Like every SAP product, it is rigid with product strategy and hard to keep pace with advancements in technology
- Integration with open-source technologies and the future road map is always a point of contention
- Costs
Return on Investment
- Improved governance around data acquisition and data management
- Almost 20 to 25% savings in managing the data pipelines from operations point of view
- More focus on bringing additional external sets of data into the landscape for AI / ML processes
Alternatives Considered
Informatica API Manager
Usability
Other Software Used
SAP BW/4HANA, Snowflake, Databricks Data Intelligence Platform
SAP Data Intelligence's analytics have a leg up on the competition.
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
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
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
