We performed a comparison between erwin Data Intelligence by Quest and SAS Data Management based on real PeerSpot user reviews.
Find out in this report how the two Data Governance solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The data management is, obviously, key in understanding where the data is and what the data is. And the governance can be done at multiple levels. You have the governance of the code sets versus the governance of the business terms and the definitions of those business terms. You have the governance of the business data models and how those business data models are driving the physical implementation of the actual databases. And, of course, you have the governance of the mapping to make sure that source-to-target mapping is done and is being shared across the company."
"Mind map... is a really good feature because it is very helpful in seeing which column's tables are related. Also, you can flag them with "sensitive data" and other indicators. You can also customize your own features for the mind map. That was another very robust feature."
"We always know where our data is, and anybody can look that up, whether they're a business person who doesn't know anything about Informatica, or a developer who knows everything about creating data movement jobs in Informatica, but who does not understand the business terminology or the data that is being used in the tool."
"Data Intelligence creates a single source of truth for all of our metadata. This solution is better for data warehousing, but the metadata features speed up our development work. It's easy to create and manage mappings because we can export them to Informatica and pick up the work where we left off."
"Overall, DI's data cataloging, data literacy, and automation have helped our decision-makers because when a source wants to change something, we immediately know what the impact is going to be downstream."
"The interface is easy to use. I also like Erwin's automatic data classification and data quality checks."
"The solution saves time in data discovery and understanding our entire organization's data."
"The possibility to write automation scripts is the biggest benefit for us. We have several products with metadata and metadata mapping capabilities. The big difference when we were choosing this product was the ability to run automation scripts against metadata and metadata mappings. Right now, we have a very high level of automation based on these automation scripts, so it's really the core feature for us."
"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."
"The technical support is excellent."
"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."
"I am impressed with the tool's ability to customize."
"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."
"The tool is reliable, quick, and powerful."
"If we are talking about the business side of the product, maybe the Data Literacy could be made a bit simpler. You have to put your hands on it, so there is room for improvement."
"The SDK behind this entire product needs improvement. The company really should focus more on this because we were finding some inconsistencies on the LDK level. Everything worked fine from the UI perspective, but when we started doing some deep automation scripts going through multiple API calls inside the tool, then only some pieces of it work or it would not return the exact data it was supposed to do."
"The integration with various metadata sources, including erwin Data Modeler, isn't smooth in the current version. It took some experimentation to get things working. We hope this is improved in the newer version. The initial version we used felt awkward because Erwin implemented features from other companies into their offering."
"The metadata ingestion is very nice because of the ability to automate it. It would be nice to be able to do this ingestion, or set it up, from one place, instead of having to set it up separately for every data asset that is ingested."
"The versioning can sometimes be confusing because we use the publishing feature for the mapping. Technical analysts sometimes have two versions, and they should know that the public version is the correct one."
"The data quality assessment requires third-party components and a separate license."
"We chose to implement on an Oracle Database because we also had the erwin Data Modeler and Web Portal products in-house, which have been set up on Oracle Databases for many years. Sometimes the Oracle Database installation has caused some hiccups that wouldn't necessarily have been caused if we had used SQL Server."
"There may be some opportunities for improvement in terms of the user interface to make it a little bit more intuitive. They have made some good progress. Originally, when we started, we were on version 9 or 10. Over the last couple of releases, I've seen some improvements that they have made, but there might be a few other additional areas in UI where they can make some enhancements."
"The solution could use better documentation."
"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."
"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."
"The solution is quite expensive and hard to install/configure."
"I would like the tool to include the ability to automate the modifications of the integrations."
"The pricing of the solution needs to be improved. They need to work to make it more affordable."
"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."
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erwin Data Intelligence by Quest is ranked 4th in Data Governance with 18 reviews while SAS Data Management is ranked 28th in Data Governance with 15 reviews. erwin Data Intelligence by Quest is rated 8.6, while SAS Data Management is rated 8.4. The top reviewer of erwin Data Intelligence by Quest writes "Enabled us to centralize a tremendous amount of data into a common standard, and uniform reporting has decreased report requests". On the other hand, the top reviewer of SAS Data Management writes "A scalable solution with customer support that is responsive and diligent". erwin Data Intelligence by Quest is most compared with Microsoft Purview Data Governance, Collibra Governance, Alation Data Catalog, Informatica Axon and Collibra Lineage, whereas SAS Data Management is most compared with Informatica PowerCenter, Tungsten RPA, Microsoft Purview Data Governance, SSIS and IBM InfoSphere DataStage. See our SAS Data Management vs. erwin Data Intelligence by Quest report.
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