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."
"The interface is easy to use. I also like Erwin's automatic data classification and data quality checks."
"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."
"There is a wide range of widgets that enables the user to find the proper information quickly. The presentation of information is something very valuable."
"Data Intelligence has provided more profound insights into legacy data movements, lineages, and definitions in the short term. We have linked three critical layers of data, providing us with an end-to-end lineage at the column level."
"It is a central place for everybody to start any ETL data pipeline builds. This tool is being heavily used, plus it's heavily integrated with all the ETL data pipeline design and build processes. Nobody can bypass these processes and do something without going through this tool."
"Data Intelligence allows us to automate multiple tasks we had previously done manually, such as restructuring the metadata for our purposes, setting up ETL flows, and defining the data tables we create. It also enables us to standardize our approach and our technical processes."
"The solution saves time in data discovery and understanding our entire organization's data."
"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."
"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."
"The technical support is excellent."
"I am impressed with the tool's ability to customize."
"If you compare it to SQL, the memory and development times are very quick."
"The product offers very good flexibility."
"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."
"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."
"There is room for improvement with the data cataloging capability. Right now, there is a list of a lot of sources that they can catalog, or they can create metadata upon, but if they can add more then that would be a good plus for this tool."
"Everything about Data Intelligence is complex. Though we've used the tool for five years, we're still only using about 30 to 40 percent of its capabilities. It would be helpful if we could customize and simplify the user interface because there are so many redundant things."
"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 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."
"There was a huge learning curve, and I'd been in software development for most of my career. The application itself, and how it runs menus and screens when you can modify and code, is complex. I have found that kind of cumbersome."
"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."
"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."
"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."
"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."
"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."
"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."
"The solution could use better documentation."
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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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