SAP Data Intelligence vs. SAS Data Management

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
SAP Data Intelligence
Score 8.5 out of 10
N/A
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.N/A
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.N/A
Pricing
SAP Data IntelligenceSAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
SAP Data IntelligenceSAS Data Management
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional Details
More Pricing Information
Features
SAP Data IntelligenceSAS Data Management
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
SAP Data Intelligence
-
Ratings
SAS Data Management
8.3
10 Ratings
1% above category average
Connect to traditional data sources00 Ratings8.610 Ratings
Connecto to Big Data and NoSQL00 Ratings8.19 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
SAP Data Intelligence
-
Ratings
SAS Data Management
6.7
8 Ratings
22% below category average
Simple transformations00 Ratings6.18 Ratings
Complex transformations00 Ratings7.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
SAP Data Intelligence
-
Ratings
SAS Data Management
6.7
8 Ratings
19% below category average
Data model creation00 Ratings5.56 Ratings
Metadata management00 Ratings7.47 Ratings
Business rules and workflow00 Ratings6.67 Ratings
Collaboration00 Ratings7.07 Ratings
Testing and debugging00 Ratings6.17 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
SAP Data Intelligence
-
Ratings
SAS Data Management
7.9
9 Ratings
4% below category average
Integration with data quality tools00 Ratings7.69 Ratings
Integration with MDM tools00 Ratings8.27 Ratings
Best Alternatives
SAP Data IntelligenceSAS Data Management
Small Businesses

No answers on this topic

Skyvia
Skyvia
Score 9.6 out of 10
Medium-sized Companies

No answers on this topic

IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
Enterprises
Talend Data Fabric
Talend Data Fabric
Score 9.4 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
SAP Data IntelligenceSAS Data Management
Likelihood to Recommend
8.1
(54 ratings)
7.6
(11 ratings)
Likelihood to Renew
8.2
(2 ratings)
9.0
(2 ratings)
Usability
7.1
(49 ratings)
6.0
(2 ratings)
Performance
-
(0 ratings)
9.0
(1 ratings)
Support Rating
7.3
(46 ratings)
7.7
(6 ratings)
Configurability
8.2
(1 ratings)
-
(0 ratings)
Vendor post-sale
9.1
(1 ratings)
-
(0 ratings)
Vendor pre-sale
9.1
(1 ratings)
-
(0 ratings)
User Testimonials
SAP Data IntelligenceSAS Data Management
Likelihood to Recommend
SAP
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.
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SAS
When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
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Pros
SAP
  • 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.
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SAS
  • SAS/Access is great for manipulating large and complex databases.
  • SAS/Access makes it easy to format reports and graphics from your data.
  • Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
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Cons
SAP
  • 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.
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SAS
  • Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
  • Debugging errors from the logs is a complicated process.
  • E-mail alert system is very primitive and needs customization to make it more modern,
  • Cannot send SMS alerts for jobs.
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Likelihood to Renew
SAP
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
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SAS
We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
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Usability
SAP
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.
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SAS
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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Performance
SAP
No answers on this topic
SAS
It worked as expected.
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Support Rating
SAP
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,
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SAS
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
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Alternatives Considered
SAP
One of the reasons to pick SAP Data Intelligence is the speed and security it provides, in addition to the excellent support it provides. It is also compatible with all popular databases, which is another reason to choose it.
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SAS
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
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Return on Investment
SAP
  • 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.
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SAS
  • We have more users who can connect to the many different data sources.
  • Our users do have existing SAS programming knowledge and that can carry over.
  • Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.
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ScreenShots

SAP Data Intelligence Screenshots

Screenshot of Business GlossaryScreenshot of Example of data quality operatorsScreenshot of Data profiling fact sheetScreenshot of SAP Data Intelligence Jupyter lab notebook for machine learningScreenshot of SAP Data Intelligence data pipeline using PythonScreenshot of SAP Data Intelligence example ata quality dashboard