IBM Cloud Pak for Data

My primary use case for Cloud Pak is that I am the reference Data steward for the Africa regions in the banks where I work. My main objective is to capture the reference data in Caltech or Data and ensure that people profile or QA their data. 

This is due to the fact that a large percentage of data is actually reference data, not by volume, but by the number of tables. The group-approved reference data is used to assure quality and ensure people know what they have; that's my primary use case for Cloud Pak.

There's a whole bunch of stuff I really like. I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography. Those base-level data management components, together with the reference data, can then be reused whether I want to figure out where the data is coming from—using Nantucket, for example—or checking the quality of my data. 

Often, when I check the quality of my data, I might find an issue, but that data did not originate in the system where I found the issue. So, I need to use Nantucket to track back to where that data originally came from so I can fix it at the source. I love that component of Cloud Pak. 

I do not do much with the machine learning or AI pieces. It is probably because I can start at a basic level with data management: policies, rules, categories, reference data, and business terms. From there, I can work my way into a more granular level, applying all of that information on top of my actual data to understand what my data looks like, where it came from, and where it went wrong, managing it throughout the cycle.

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. 

There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. 

They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. 

It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE  models. The data modeling component is available in Cloud Pak. 

Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

I have used the solution since the end of 2021.

Scalability is endless if I can pay for it. Obviously, it is just for containers, however, I have to pay more.

The response time is quick, however, solving the problem is not always as fast. Cloud Pak is a complicated system, and it's often difficult to find the right resource in IBM to help with specific issues.

Neutral

The setup was very complete and very complex.

We did the implementation with IBM.

The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.

I've looked at Talend, Calibra, Denodo , Purview , and AWS Glue . It depends on the client's maturity in data management. If the client is only looking to do data quality as a small piece of data management, Denodo  would be an excellent choice. If they are looking for end-to-end data management and have the technical resources to get Cloud Pak running and enabled with all functionalities, then definitely Cloud Pak. The choice depends on the maturity of the company.

Cloud Pak is a very, very, very good system. I'm super impressed with it. The learning curve is high, but I gain so much when I finally  figure it out. 

Overall product rating: seven out of ten.

IBM

What do you like best about the product?

The platform to integerate multiple tools that ease the integeration and processing from end to end makes the high usage. easy to use and great support team.

What do you dislike about the product?

can reduse the cost of the service will improve the frequency of usage

What problems is the product solving and how is that benefiting you?

end to end integeration and the embedded ai helps to use it

What do you like best about the product?

IBM Cloud Pak for Data has become an essential tool in driving our organization's digital transformation. The platform's comprehsnive integrated approach to data management, governance, analaytics, and AI has signifcantly streamlined our data operations and empowered us to make data-driven decisions with confidence.

What do you dislike about the product?

While the value proposition of IBM Cloud Pak for Data is undeniable, the initial setup and configuration can be complex and time-consuming, requiring dedicated resources and expertise.

What problems is the product solving and how is that benefiting you?

IBM Cloud Pak for Data has been instrumental in streamlining our data operations. Its unified platform for integration, governance, and AI-powered analytics has broken down silos, mitigated risk, and enhanced our ability to derive actionable insights for improved decision-making and competitive advantage.

IBM Watson Catalog and data pipelines are the most valuable features of the solution.

Previously, we used to extract the information in the DSX and the XML formats. IBM Cloud Pak for Data exports information mostly on the ISX, which is an encrypted format. The only challenge with the tool is the metadata queries we try to understand.

We have to go with the lineage and other packages that come with IBM. Previously, we created our own reports depending on the existing command line export of the mappings. The solution's catalog searching or map search needs to be improved.

I have been using IBM Cloud Pak for Data for two years.

We usually recommend the solution for medium and large-scale organizations.

My current organization is a Gold Partner with IBM. Whenever we reach out to the support team, the turnaround time is about 24 to 48 hours, which is pretty decent.

I rate the solution’s technical support an eight to nine out of ten.

Positive

The solution’s initial setup is easy.

The solution's pricing is competitive with that of other vendors. The pricing also depends on the number of users.

If people are with the existing stuff, I would definitely suggest they go with IBM Cloud Pak for Data. I usually recommend the solution for the financial sector, where I worked for about ten years. I worked with IBM for almost eight years. Unless they want to migrate to a new product completely, I recommend IBM Cloud Pak for Data to explore current business. It is easy to integrate the tool with other solutions.

Except for metadata queries, metadata validations, and metadata integrations, I don't see any issues with the solution. I would recommend the solution to other users if it supports their existing infrastructure.

Some people don't want to put their data in the cloud because they are concerned about how the data is secured with encryption and decryption. For such cases, we have listed out all the pros and cons of the solution to suggest them to users.

Overall, I rate the solution a seven out of ten.

What do you like best about the product?

Unifying siloed data across our projects into a central platform has been fantastic. This capability has been invaluable, enabling us to consolidate disparate data sources, identify critical trends, and optimize resource allocation with percise.

What do you dislike about the product?

While IBM CP4D offers powerful integration and AI-driven insights, the inital setup complexisty can be daunting, requiring substantial IT expertise. Also, updates occasionally disrupt ongoing workflows, necessitating careful planning and testing to mitigate impacts.

What problems is the product solving and how is that benefiting you?

Unifying our data has transformed our project management. It enhances collaboration aross teams, boosts productivity, and accelerates decision-making, crucial in our dynamic construction projects.