We performed a comparison between erwin Data Intelligence by Quest and SAS Data Governance based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Collibra, Informatica and others in Data Governance."The data mapping manager is the most valuable feature."
"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."
"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."
"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."
"The biggest benefit with erwin DI is that I have a single source of truth that I can send anybody to. If anybody doesn't know the answer we can go back to it. Just having a central location of business rules is good."
"The biggest impact for us is that erwin generates DDL extremely quickly. We're able to pull in metadata, map it to a target, generate DDL to create the tables, and generate SSIS packages. Previously, especially going back 10 to 15 years ago, hundreds of hours had to be spent to manually perform these tasks. This solution completely automates it and gets it 90% done. We can then pass it off to a developer to create the items in SSIS."
"Being able to capture different business metrics and organize them in different catalogs is most valuable. We can organize these metrics into sales-related metrics, customer-related metrics, supply chain-related metrics, etc."
"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."
"It is a very professional product. Scalability-wise, I rate the solution a ten out of ten."
"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 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 technical support could be improved."
"We still need another layer of data quality assessments on the source to see if it is sending us the wrong data or if there are some issues with the source data. For those things, we need a rule-based data quality assessment or scoring where we can assess tools or other technology stacks. We need to be able to leverage where the business comes in, defining some business rules and have the ability to execute those rules, then score the data quality of all those attributes. Data quality is definitely not what we are leveraging from this tool, as of today."
"Really huge datasets, where the logical names or the lexicons weren't groomed or maintained well, were the only area where it really had room for improvement. A huge data set would cause erwin to crash. If there were half a million or 1 million tables, erwin would hang."
"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."
"It's a little bit clunky. I think a lot of these features were bolted on, and they don't necessarily transition smoothly in the interface. I would like to see a little more cohesion."
"The data quality assessment requires third-party components and a separate license."
"In today's time, to be competitive, the solution's price should be lowered."
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erwin Data Intelligence by Quest is ranked 4th in Data Governance with 18 reviews while SAS Data Governance is ranked 14th in Data Governance with 1 review. erwin Data Intelligence by Quest is rated 8.6, while SAS Data Governance is rated 10.0. 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 Governance writes "An exceptionally stable and scalable product that helps businesses in the area of data integrity". 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 Governance is most compared with .
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