SAP Data Intelligence vs. SAP Information Steward

It helps our BUs analyze data and create dashboards they can understand. While slowing down with a large database, it becomes less helpful. In my experience, it is excellent in consolidating information from several sources for analysis, decision-making, and knowledge gaps. Excellent at managing information access.

Incentivized

In data conversion scenarios, the tool can be used for data profiling, data quality and data verification jobs. However, implementation depends on what implementation strategy or approach the company is adopting. In real-time scenarios, the tool can be used for generating data profiling and data quality reports as well. Business rules for data quality checks can be built into the tool and can be assigned to end or business users.

Incentivized

• It integrates well with our current ecosystem of SAP products, like HANA.
• It provides end-to-end machine learning operations, with tools for the complete model life cycle.
• It has a simple user interface for novice users, with complex tools also available for power users.
• It builds on SAP Data Hub, providing all the ETL functions of that tool with additional machine learning functionality.
• It can run in the cloud, no on-premise software management needed.
• Many programming languages are supported, it provides a sandbox environment for the user to develop in whichever style they prefer.
• SAP is very actively developing and improving it.

Incentivized

• Data Profiling
• Data Quality Monitoring
• Dashboards

Incentivized

• Data transfer speed tends to be slow when there is poor internet connection since SAP Data Intelligence don’t synchronize data while offline. However, this is not vendor fault, that’s why we have implemented robust wireless technology internet connection in our organization.

Incentivized

• More real-time integration scenarios needed.
• Needs more generic standard content for metadata management.
• The user interface can be more intuitive based on AI.

Incentivized

Allow collaborations among various personas
with insights as ratings and comments on the
datasets Reuse knowledges on the datasets for new users Next-Gen Data Management and Artificial Intelligence

Incentivized

Out of the box solution

Incentivized

Good tool with lots of potential, but I still see a lot of room for improvement, e.g. when it comes to debugging functionality to understand exactly where pipelines fail and what the data at that point looks like (similar to BW debugging). Also, I am missing SAPs standard machine learning libraries (Python) to be pre-installed, among some other general usability improvements.

Incentivized

It provides out of box solution for information management at organisation level

Incentivized

Initially we struggle to get help from SAP but then dedicated Dev angel was assigned to us and that simplify the overall support scenario. There is still room of improvement in documentation around SAP Data intelligence. We struggle a lot to initially understand the feature and required help around performance improvement area,

Incentivized

I believe many features from SAP Information Steward are available in other SAP products as well hence it is more confusing for business or customers to do the right selection. Moreover SAP strategy is not very clear for this particular product hence often we are confused while exploring more related scenarios

Incentivized

Ready recknoer tools that act as reference are missing that can help to formulate ;Decision Driven Framework' for various strategic decesions

Incentivized

Since we are big on SAP ecosystem products in our IT landscape, it was natural for us to find a best possible solution from SAP product suite. However, we still explored the products available from Informatica product portfolio, we found using SAP Data Intelligence more prudent in terms of seamless integration with lot of our other SAP products.

Incentivized

In the case of this organization, Information Steward was part of a suite from SAP together with Data Services and SAP Master Data Governance. In terms of the overall package it was worth it for the company. Informatica cost was higher and the overall benefit from SAP package was the key decision point.

Incentivized

• Automation of data management slashed tasks by over 60% in most departments for the first 8 months.
• Metadata catalogs have enabled us to categorize data from disjointed sources in one place.
• It runs multiple ML models which enhances flexibility when managing data.

Incentivized

• Improved data flaws
• Catching mistakes in data
• Reduced technical errors

Incentivized