Cloud Pak for Data with Netezza
Overall Satisfaction with IBM Cloud Pak for Data
We advise many of our clients on the best ways to process ETL and Analytics, quickly, and efficiently. CP4D has been around for many years and we have implemented this for many organizations. It solves most bottlenecks clients have for processing in a very cost effective and reliable environment. Clients can also process jobs within seconds where it would previously take days. This offers a platform to organizations allowing them to change their business models. For example, a large financial institution in Canada would normally score their customers in 45 hours. With CP4D with Netezza, the same scoring job completes in 15 seconds. Now customers can be scored daily. This same story can be seen at hundreds of other clients we support. There is nothing else like it on the market at such a competitive price on premise or in the cloud.
Pros
- the fastest execution of queries
- business critical support and redundancy in design for almost 100% uptime
- ties in with many other IBM offerings such as Watson
- support at IBM is unbeatable with experts available before and after the sale to assist clients
Cons
- 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.
- Ease of use
- Fast Analytics
- Easy to train staff how to use
- Incredible ROI for clients
- Simple for users to understand and use
- No downtime for analytics processing
- VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ and Tanzu SQL)
IBM has healing mechanisms when resource usage is high. This platform performs well, but when it runs out of capacity, it has crashed for many clients. This is innate in its original design.
Do you think IBM Cloud Pak for Data delivers good value for the price?
Yes
Are you happy with IBM Cloud Pak for Data's feature set?
Yes
Did IBM Cloud Pak for Data live up to sales and marketing promises?
Yes
Did implementation of IBM Cloud Pak for Data go as expected?
Yes
Would you buy IBM Cloud Pak for Data again?
Yes
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