IBM Cloud Pak for Data Reviews

Vendor: IBM

4.0 out of 5

12 reviews
85% willing to recommend

What is IBM Cloud Pak for Data?

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

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IBM Cloud Pak for Data is the #3 ranked solution in top Data Virtualization solutions and #18 ranked solution in top Data Integration Tools. PeerSpot users give IBM Cloud Pak for Data an average rating of 8.0 out of 10. Based on the analysis of the 12 most recent IBM Cloud Pak for Data reviews, the overall sentiment is positive, with a sentiment score of 6.7. (Among the highest in the category). IBM Cloud Pak for Data is most commonly compared to SAP HANA: IBM Cloud Pak for Data vs SAP HANA. IBM Cloud Pak for Data is popular among the large enterprise segment, accounting for 75% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 28% of all views.

Buyer's Guide

IBM Cloud Pak for Data

November 2024

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Featured reviews

Murali B

Associate Manager at Ernst & Young

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.

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Murali B

Associate Manager at Ernst & Young

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.

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Drew Collins

Freelance Innovation & Delivery at DMC

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. Also, currently, we do not have any plans in our company to increase the number of uses using the solution. However, the product is being used extensively in our company.

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IBM Cloud Pak for Data mindshare

Product category:

As of November 2024, the mindshare of IBM Cloud Pak for Data in the Data Virtualization category stands at 17.7%, up from 13.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Data Virtualization

Key learnings from peers

Last updated Nov 21, 2024

Valuable Features

Data virtualization, reporting, Watson Studio, Watson Machine Learning, Watson Knowledge Catalog, containerization, IBM MQ, IBM App Connect, IBM API Connect, ISPF, Modeler flows, data quality and ETL tools, data stage component, data preparation capabilities, artificial intelligence algorithms, and data pipelines are valuable features of IBM Cloud Pak for Data.

"IBM Watson Catalog and data pipelines are the most valuable features of the solution."
"DataStage allows me to connect to different data sources."
"Its data preparation capabilities are highly valuable."

Room for Improvement

IBM Cloud Pak for Data needs to reduce system resource usage. Improving technical support is necessary. Users would benefit from a "lite" version for smaller companies. Simplifying the installation and administration process is crucial. Enhancing integration with other cloud service providers, connectors, and features like data curation is important. Issues with performance, interface delays, native features being decommissioned, and complexity in shifting from on-premise to cloud need addressing.

"The solution's catalog searching or map search needs to be improved."
"The product must improve its performance."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."

ROI

Users experienced significant time savings and cost reduction from IBM Cloud Pak for Data. It simplified data management, resulting in faster insights and improved decision-making. Integration capabilities allowed smoother workflows and reduced manual processing. Automation features increased efficiency and minimized errors. Enhanced data governance helped mitigate risks, contributing to a better return on investment. The ability to scale resources dynamically catered to varying business requirements, providing flexibility and economic advantages.

Pricing

IBM Cloud Pak for Data's pricing is often seen as high, with a subscription-based yearly license. While some find the cost competitive compared to Informatica and Precisely, others argue it's too expensive, especially for smaller companies. The pricing, often deemed fair for its functionality, includes standard license fees without extra charges. Larger enterprises may find the value justifiable, although overall costs and execution remain a concern for many.

"The solution's pricing is competitive with that of other vendors."
"The solution is expensive."
"It's quite expensive."

Popular Use Cases

Consultancy companies use IBM Cloud Pak for Data for data integration and advising clients. It is utilized in machine learning, data science, and creating data catalogues. FinTech and banking sectors deploy it for developing models like credit scoring and fraud control. Others focus on artificial intelligence, spend analytics, and contract analytics, particularly managing category strategies and supplier relationships. Projects in Mexico involve sales projections and store product renewals.

Service and Support

Customer service and support of IBM Cloud Pak for Data receive mixed feedback. Some find it helpful, with ratings between seven and nine out of ten, while others highlight slow response times. Organizations with direct connections to IBM report better experiences, although some note delays in ticket resolutions. Support is described as sufficient and strong enough without needing extra effort.

Deployment

IBM Cloud Pak for Data's initial setup is complex and requires expertise. Integrating with different cloud services can be tricky. Users found the installation process not user-friendly and needing significant improvement. Deploying the platform can take months, and technical knowledge of containers and OpenShift is necessary. Some found it easier when leveraging external deployment assistance, while others noted connecting data sources as cumbersome. The ease of setup varies by deployment environment and user familiarity.

Scalability

Users have found IBM Cloud Pak for Data scalable, with some rating its scalability as high as ten out of ten. It supports easy expansion via cloud infrastructure and containerization. Organizations currently using it report no significant issues with scaling. However, some users note it can be resource-intensive, and a few are still in the evaluation phase, assessing its full scalability potential. Generally recommended for medium to large-scale organizations.

Stability

IBM Cloud Pak for Data is generally stable. Users rate its stability between seven and nine out of ten. Some note that, like many large packages comprised of various tools, stability can be an issue, but they expect improvements over time. Companies testing the enterprise version agree it is stable. Most agree on its reliability, though some mention current issues needing resolution.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

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Review data by company size

By reviewers

By visitors reading reviews

Top industries

By visitors reading reviews

Financial Services Firm

28%

Computer Software Company

11%

Manufacturing Company

Government

Insurance Company

University

Educational Organization

Energy/Utilities Company

Healthcare Company

Retailer

Transportation Company

Wholesaler/Distributor

Comms Service Provider

Construction Company

Logistics Company

Non Profit

Media Company

Real Estate/Law Firm

Hospitality Company

Legal Firm

Wellness & Fitness Company

Consumer Goods Company

Recreational Facilities/Services Company

Outsourcing Company

Performing Arts

Aerospace/Defense Firm

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Learn more about IBM Cloud Pak for Data

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM Cloud Pak for Data was previously known as Cloud Pak for Data.