We performed a comparison between Oracle Data Quality and SAS Data Management based on real PeerSpot user reviews.
Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality."I have found the most valuable features to be data cleansing and deduplication."
"Once it is set up, it is easy to use and maintain."
"The features I like most about Oracle Data Quality include extraction, transformation, and validation, which makes it a multipurpose product such as Oracle GoldenGate and Oracle Data Integrator. I also like that Oracle Data Quality is very fast, so you can use it for a large volume of data within a short period. You have to do the validation very quickly, so the solution helps in that area of data quality. Another feature of Oracle Data Quality that I like is the MDM (Master Data Management) where you'll have a single source of protection, and this makes the solution perfect and helpful to my company."
"With Oracle Data Quality, the most valuable feature is entity matching."
"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."
"The technical support is excellent."
"If you compare it to SQL, the memory and development times are very quick."
"I am impressed with the tool's ability to customize."
"The product offers very good flexibility."
"This is an established product with powerful data analysis and varied options for user entry points."
"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."
"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."
"Oracle Data Quality should integrate with data warehousing solutions such as Azure and CWS Office. For example, having the ability to integrate with tools, such as Azure Synapse and SQL data warehousing would be a great benefit."
"Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution."
"Oracle is currently not that intuitive. We need to use programmers to write code for a lot of the procedures. We need to have them write CL SQL code and write a CL script."
"If the length of time required for deployment was reduced then it would be very helpful."
"The solution is quite expensive and hard to install/configure."
"The pricing of the solution needs to be improved. They need to work to make it more affordable."
"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 could use better documentation."
"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."
"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."
"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."
Oracle Data Quality is ranked 10th in Data Quality with 8 reviews while SAS Data Management is ranked 13th in Data Quality with 15 reviews. Oracle Data Quality is rated 8.4, while SAS Data Management is rated 8.4. The top reviewer of Oracle Data Quality writes "Fast, has good extraction, validation, and transformation features, and provides good support". On the other hand, the top reviewer of SAS Data Management writes "A scalable solution with customer support that is responsive and diligent". Oracle Data Quality is most compared with Informatica Data Quality, whereas SAS Data Management is most compared with Informatica PowerCenter, Tungsten RPA, Microsoft Purview, Palantir Foundry and IBM InfoSphere DataStage.
See our list of best Data Quality vendors.
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.
