IBM Cloud Pak for Data vs. IBM InfoSphere Information Server

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

Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.

• Increases our impact by combining BI skills with advanced analytics and machine learning in an easy to use visual interface.
• Visualization and reporting.
• Rapidly provides business -ready data to all users equally.
• Manage data spread across distributed stores and clouds.

Incentivized

• IIS best for ETL ,not ELT , and many and diffrent source systems.
• It also can process big data , unstuctured data
• It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems

Incentivized

• Cannot save changes to some secrets in the internal vault
• Sign-in issues on environments where IAM is enabled
• The Enforce quotas option is disabled

Incentivized

• I would be nice to have a new web development environment for DataStage.
• Connectivity Packs such as Pack for SAP Application are a little pricey.
• It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.

Incentivized

• Scale of implementation
• IBM techsupport

Incentivized

IBM Cloud Pak for Data takes the IBM Cognos solution and provides this on an enterprise cloud platform that can be extended to support better data integration and data science capabilities.

Incentivized

DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS

• We have the ability to access all our data much quicker through the unified search option.
• 30% increase in productivity through the introduction of AI.
• Improved data security and governance.

Incentivized

• Productivity of the development of integration processes.
• Better documentation and governance.
• Reduce training costs of various technologies.