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Great all in one tool for data
What do you like best about the product?
It is pretty easy to understand by people who are not very proficient in tech as well, and that makes it a very powerful tool.
This being a one-stop solution for your data and analytics needs, helps users in achieving optimal performance in their analytical and other tasks.
This being a one-stop solution for your data and analytics needs, helps users in achieving optimal performance in their analytical and other tasks.
What do you dislike about the product?
As containerization is still comparatively fairly new, it can be a bit difficult for everyone to understand and use it since cloud pak is mostly based on it. So, maybe if some other vertical is available for the users with lesser knowledge about it and better documentation, can help.
What problems is the product solving and how is that benefiting you?
There are several data integration challenges with a lot of data sources, cleaning and preparing the data and making it available for the analytics pipeline later on, in order to get correct analysis. Also, need to maintain the security in data on the cloud. Also, few verticals require ML and AI capabilities for different kinds of predictions as well
IBM Cloud Pak - All-in-one hybrid cloud platform. Achieve better business performance.
What do you like best about the product?
Cloud Pak can use AWS services and features. Cloud-native development solution. Provide a secure way of cloud. Security. Hybrid cloud. Helps with data preparation for artificial intelligence. Collect, organize and analyze data, irrespective of where that data actually resides.
What do you dislike about the product?
Not that famous in the industry yet. Not very user-friendly. Multi-user login can be granted. Implementation is not that simple. Documentation and videos are limited.
What problems is the product solving and how is that benefiting you?
All-in-one hybrid cloud platform. Business automation. Help to provide security for the cloud environment. Helps to get info about potential risks and respond faster to those threats.
Review for IBM Cloud Pak for Data
What do you like best about the product?
With the help of automation and embedded AI, it helps data to be easily identified thus a great boon to data-driven business
What do you dislike about the product?
Service issues like backup and restore and sometimes installation and backup issues make it a little tedious
What problems is the product solving and how is that benefiting you?
Creating connectors to link the data of the organization with IBM Cloud Pak for Data
Great tool for Enterprise level Data Insights and much more
What do you like best about the product?
A lot of great features are provided by IBM tools. And cloud Pak for Data in particular is again something that comes with a bundle of great data-centric features, which makes the life of a data team easier in several aspects.
Data virtualization has been very useful, along with the ability to integrate with several other tools, as and when required.
Also, containerization is very crucial in maximum projects these days, and IBM cloud pak beautifully delivers this feature as well and helps in creating a lesser error-prone environment for everyone and giving faster deliveries and insights.
Data virtualization has been very useful, along with the ability to integrate with several other tools, as and when required.
Also, containerization is very crucial in maximum projects these days, and IBM cloud pak beautifully delivers this feature as well and helps in creating a lesser error-prone environment for everyone and giving faster deliveries and insights.
What do you dislike about the product?
I feel it is a bit complex and pricey though, and hence not easily approachable to integrate into smaller firms.
From the complexity perspective, it is because it offers tonnes of amazing features, but it becomes equally difficult to get a hang of everything and understand each feature and takes some time to get used to. So, maybe more tutorials and all should be there for better understanding and making knowledge transfer smooth for everyone
From the complexity perspective, it is because it offers tonnes of amazing features, but it becomes equally difficult to get a hang of everything and understand each feature and takes some time to get used to. So, maybe more tutorials and all should be there for better understanding and making knowledge transfer smooth for everyone
What problems is the product solving and how is that benefiting you?
Needed a hybrid cloud solution as our project required pulling data from several sources like DB, flat files, APIs etc. After that of course it needed to be staged and prepared and transformed accordingly as per the requirements and had to be made for different kinds of data analytics and insights generation. Then it was loaded to different targets, again according to the sub-stream it belonged to and w.r.t the end user. So, there would be a different kind of end-users, looking at the different granularity of the data.
A good business solution proposal
What do you like best about the product?
The final interface of the system is excellent because users who are not IT experts quickly learn how to use the system.
The UX was well used in this product/system.
The UX was well used in this product/system.
What do you dislike about the product?
Often corporate solutions try to look simple, but corporate environments are not. The propaganda that you can quickly: build, test, approve and maintain an environment like this. It is not easy, much less fast, because the bureaucracy and financial costs of corporate environments are high. So implementing projects like this takes months, if not years.
What problems is the product solving and how is that benefiting you?
It shares the same problems as the competition, and it promises miraculously quick and efficient solutions. But the reality is not that they are projects with a high level of complexity to achieve the promised result in advertising.
Recommendations to others considering the product:
Like any other product in this segment, you're going to hate the implementation/deploy step. But after a lot of suffering to make the integrations with the other systems of the corporation. Ah, a good product.
Cp4D platform
What do you like best about the product?
One-stop shop for all Analytics needs from collecting to analyzing allowing users to have everything needed to achieve optimal performance without affecting the underlying sources.
What do you dislike about the product?
Need to have open shift skills (container technology), requires more of a culture shift. It’s good in the long run but harder for users newer to containerization
What problems is the product solving and how is that benefiting you?
Getting faster time to value by having everything needed for a proper ad hoc analysis. Then as we adopt ML & AI capabilities we have the tools necessary to create, test, deploy, and manage those models.
Recommendations to others considering the product:
Launching a new Analytics project, this is a one UI integrating all the tools needed on the backend for a fully governed and functional Analytics environment
A good framework for data analytics and more
What do you like best about the product?
Rich with many features like data virtualization, integrations with many tools, unique way of data processing, etc. Not only that CPD has integrations with many external tools it as it runs on kubernetes we can bring in any kind of process or tool into the cluster with some work.
Also IBM team supported very well throughout the process. They even let us use their sandbox for while until we get comfortable with the system.
Also IBM team supported very well throughout the process. They even let us use their sandbox for while until we get comfortable with the system.
What do you dislike about the product?
Cost of the tool is not that approachable for smaller companies. I guess just like other IBM tools even this comes with certain cost. Another important factor to consider is its complexity. As there are many feature it brings in more complexity to the tool. It will take some time/training to understand all the aspects of this tool.
What problems is the product solving and how is that benefiting you?
We are trying to solve media related data processing problem using CPD. It involved pulling data from various sources like S3, databases, SFTP, even file uploads. Once the data from different sources are available in the system it has to be cleansed, transformed and made available for analytics at its lowest granularity. From their it would go into different paths - aggregation of the data for visualization by business teams while some folks would be using the raw data fore deep analytics.
Recommendations to others considering the product:
Its a good tool with many features... if your team likes it and fits you requirement list + budget then I would recommend it.
An end-to-end data and AI stand with data supervision, governance, and analytics capacities
What do you like best about the product?
The latest IBM Cloud Pak design is, at its focus, a distinct method of bundling and acquiring it. In this design, you can purchase up your current pieces and have all your new bundled title (merging some merchandise to a separate section product in many circumstances) plus get access to a new bundle for AWS red hat. Also, there are specific unique abilities and provisions only obtainable in the Cloud Pak licensing design, and this is particularly relevant regarding the Automation range. The product efficiently reacts to increasing controls with embedded, advanced governance skills; these combine automated detection and analysis of data, cloaking raw data, data zones, and documents life period control. It expedites utilization growth and deployment with a multi-cloud data program that is agile, flexible, and compact. The interest of Kubernetes containerization is to implement and compare services in times, somewhat of days, inside a more stable, supervised situation.
What do you dislike about the product?
If the company focuses more on the selling product in the market and makes it accessible with different other databases, it would be more adaptable and convenient to most of the industry. It explains and consolidates how you manage, secure, and interpret data to expedite data science and AI advantage. This multi-cloud stand passes a wide variety of core data microservices, with the opportunity to score more from a developing duties program. I think an excessive marketing strategy would be helpful for market gain and clients benefit both.
What problems is the product solving and how is that benefiting you?
FileNet Content Manager
Business Automation Workflow
Data Migration
Enterprise Records
Operational Decision Manager
Business Automation Workflow
Data Migration
Enterprise Records
Operational Decision Manager
Recommendations to others considering the product:
It provides the benefit and interest of a vast ecosystem of interconnected hardware, software, and services within a growing service description. Provision preferred data services flexibly and rapidly and customized data workflows to your specific requirements.
The Best way to adopt cloud inside firewall
What do you like best about the product?
I really love auto ai and jupyter lab and machine learning
What do you dislike about the product?
Maybe the experience in db2 database :) :D
What problems is the product solving and how is that benefiting you?
Price optimization and demand prediction
Recommendations to others considering the product:
Useautoai and open scale
Security is a pillar at IBM
What do you like best about the product?
IBM is a trusted partner to international businesses, providing machines to support cross-continental data compute. Having said that, IBM allows me to control my data while providing support for 50+ locations. Data governance is simplified with IBM in a true cloud model. Security is paramount and in the DNA of IBM. It has been since the entrance of IBM in the international computing market for businesses back in the 1950-60s.
What do you dislike about the product?
I'd still like to see more options to seamlessly migrate from other cloud providers to IBM and that is an area that might need some more investment.
What problems is the product solving and how is that benefiting you?
Big data sets for both internal use and for machine learning feed need a hybrid solution while maintaining the highest degree of security in the cloud that matches or outrivals that of in-house data security.
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