We performed a comparison between IBM Cloud Pak for Data and SAS Data Management based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."You can model the data there, connect the data models with the business processes and create data lineage processes."
"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."
"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."
"The most valuable features are data virtualization and reporting."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"Its data preparation capabilities are highly valuable."
"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."
"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."
"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."
"This is an established product with powerful data analysis and varied options for user entry points."
"If you compare it to SQL, the memory and development times are very quick."
"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."
"The solution could have more connectors."
"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."
"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."
"The technical support could be a little better."
"The solution is quite expensive and hard to install/configure."
"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 solution could use better documentation."
"The pricing of the solution needs to be improved. They need to work to make it more affordable."
"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."
"I would like the tool to include the ability to automate the modifications of the integrations."
"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."
IBM Cloud Pak for Data is ranked 15th in Data Integration with 11 reviews while SAS Data Management is ranked 43rd in Data Integration with 15 reviews. IBM Cloud Pak for Data is rated 8.0, while SAS Data Management is rated 8.4. The top reviewer of IBM Cloud Pak for Data writes "A scalable data analytics and digital transformation tool that provides useful features and integrations". On the other hand, the top reviewer of SAS Data Management writes "A scalable solution with customer support that is responsive and diligent". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Alteryx Designer, whereas SAS Data Management is most compared with Informatica PowerCenter, Tungsten RPA, Microsoft Purview, Palantir Foundry and Collibra Lineage.
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