IBM Cloud Pak for Data vs. SAS Data Management

IBM Cloud Pak for Data with Netezza is well suited for clients who require fast, economical analytics processing. It is not designed to be used as a transactional processing environment. For example, a large customer is using it during the point of sale process. That makes little sense in that business case. However, to take analysis to market faster, it excels well in that space.

Incentivized

When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.

Incentivized

• I really like the AI and ML which enables us to source data in different sources for easy data-driven decisions.
• It's a cloud tool that keeps all our data safe, backed up ahs obtainable at any time without being exposed to any kind of risks or loss.
• I like the fact that ICP is main based on open source stack which adds value to products like VA or MCM.
• IBM support service is great and top-class.

Incentivized

• SAS/Access is great for manipulating large and complex databases.
• SAS/Access makes it easy to format reports and graphics from your data.
• Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.

Incentivized

• This offering is currently available on prem, in Azure, and soon in AWS. GCP availability will be in the future as there is demand in the marketplace
• The on premise offering starts with a Base + 0 model, which is a significant appliance. There are no 'mini' offerings as there were in the past.
• At Destiny, we work closely with IBM to help our clients perform budgetary planning.

Incentivized

• Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
• Debugging errors from the logs is a complicated process.
• E-mail alert system is very primitive and needs customization to make it more modern,
• Cannot send SMS alerts for jobs.

Incentivized

We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.

The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.

Incentivized

It worked as expected.

Incentivized

With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.

Incentivized

Generally this tool has been very helpful and innovative because increase our workflow and collaboration using integrated multi-cloud platform. It also enables us to deploy in any flexible way like on-premises or cloud which saves time and hard disk space. It also enables us to connect, catalog, govern, transform and analyze data regardless of the area.

Incentivized

Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.

Incentivized

• IBM Cloud helps us to manage data speed across every distributed stores and clouds.
• Acts as a single unified tool which brings all our data in one place where it's safe and easy to access.
• Enables all of our data users to collaborate from a single, unified interface that supports many services that are designed to work seamless.

Incentivized

• We have more users who can connect to the many different data sources.
• Our users do have existing SAS programming knowledge and that can carry over.
• Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.

Incentivized