We performed a comparison between SAP Data Quality Management and SAS Data Management based on real PeerSpot user reviews.
Find out in this report how the two Data Quality solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Our primary use case is for us to inspect the results from the product and material, and for releasing or leaving the status of the product."
"We work with API standards or norms for internal applications, so it's essential for SSE to have tests and pass those tests according to the criteria, which makes SAP Data Quality Management very important for our products."
"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."
"If you compare it to SQL, the memory and development times are very quick."
"The technical support is excellent."
"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."
"The product offers very good flexibility."
"This is an established product with powerful data analysis and varied options for user entry points."
"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."
"I am impressed with the tool's ability to customize."
"I would like for them to develop a feature to able to record all of our inspections; so all the data can go through SAP. It's not user-friendly or easy to get further analysis, so we mostly skip this step."
"SAP Data Quality Management would be better if it directly integrates with the ME system. Right now, the company has a lot of machines on the shop floor working as a standalone, so you have to use all methods to ensure that the data interface appears on the ME system and that SAP Data Quality Management records the QM results. It would be much easier if the ME system could be integrated directly with SAP Data Quality Management."
"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."
"I would like the tool to include the ability to automate the modifications of the integrations."
"The solution is quite expensive and hard to install/configure."
"With SAS Data Management, you have to purchase an external driver, configure all of the tables for all of the data that you will extract from Salesforce. It's not a straightforward process."
"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place."
"The pricing of the solution needs to be improved. They need to work to make it more affordable."
"We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows."
"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."
SAP Data Quality Management is ranked 5th in Data Quality with 2 reviews while SAS Data Management is ranked 13th in Data Quality with 15 reviews. SAP Data Quality Management is rated 8.6, while SAS Data Management is rated 8.4. The top reviewer of SAP Data Quality Management writes "Scalable, stable, and offers good technical support". On the other hand, the top reviewer of SAS Data Management writes "A scalable solution with customer support that is responsive and diligent". SAP Data Quality Management is most compared with SAP Data Services, SAP Information Steward, Melissa Data Quality, Informatica Address Verification and Informatica Data Quality, whereas SAS Data Management is most compared with Informatica PowerCenter, Tungsten RPA, Microsoft Purview Data Governance, SSIS and IBM InfoSphere DataStage. See our SAP Data Quality Management vs. SAS Data Management report.
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We monitor all Data Quality reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.