IBM watsonx.data as a Service
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Effortless Data Handling and Seamless IBM Integration
What do you like best about the product?
i like the watsonx.data for handling data sources kinda easy. lakehouse stlye feels smooth and query performs pretty solid even data is large.
also i love how it integrates with other IBM tools, so we do not have to do extra jugglin. UI part is not perfect but clean and feels friendly UI-UX for my daily work.
it is easy to implement other IBM tools and work with it
personally we didn't need to use Customer Support but I am sure it is best as per IBM profile.
we are using for one project only in our organization, in addition we are making decision to use for other projects as well.
also i love how it integrates with other IBM tools, so we do not have to do extra jugglin. UI part is not perfect but clean and feels friendly UI-UX for my daily work.
it is easy to implement other IBM tools and work with it
personally we didn't need to use Customer Support but I am sure it is best as per IBM profile.
we are using for one project only in our organization, in addition we are making decision to use for other projects as well.
What do you dislike about the product?
i personally dislike setting up and onboarding, it takes time to connects other data sources and configuring things properly and sometime docs feels confusing.
pricing also bit higher for small teams like us, it is getting hard to make decision just because of pricing.
pricing also bit higher for small teams like us, it is getting hard to make decision just because of pricing.
What problems is the product solving and how is that benefiting you?
for us IBM watsons is solving major problem of handling too many different data sources in one place, earlier we had to manage all the data sources separately and now we are planning to move our other project in this platform also.
it helps to reduce infra overhead cost because scaling storage and compute is smooth, because of this our analytics team can give faster responses and dev team can quickly implement solution for it.
overall it saves time and saves some cost but it is bit costly also.
it helps to reduce infra overhead cost because scaling storage and compute is smooth, because of this our analytics team can give faster responses and dev team can quickly implement solution for it.
overall it saves time and saves some cost but it is bit costly also.
IBM WatsonX Efficient Capable AI Platform
What do you like best about the product?
IBM watsonx.data is a highly capable platform that includes a ton of features and capabilities. It has helped me expand my business and allowed me to tackle many more tasks than I was previously capable of
What do you dislike about the product?
IBM watsonX data has a lot of features and functionality so it can be difficult to zero in on what features you need to best serve your business use case
What problems is the product solving and how is that benefiting you?
Organization of customer data
how data be uplifted
What do you like best about the product?
easy of using and implementing, intergration
What do you dislike about the product?
should be around security and accountavility
What problems is the product solving and how is that benefiting you?
uplifting from legacy
Great experience with automation
What do you like best about the product?
it gets many unknown information from your data
What do you dislike about the product?
sometimes it is to slow and cosumes to much energy
What problems is the product solving and how is that benefiting you?
it gets a lot of our data and many unknown information
Reliable Data Platform ,Still Evolving Though
What do you like best about the product?
1.Flexible data handling and fast searches.
2. Queries run quickly and handle diverse data well.
3. I like how fast it processes and manages big data.
2. Queries run quickly and handle diverse data well.
3. I like how fast it processes and manages big data.
What do you dislike about the product?
1. Learning takes time for a beginner.
2. Initial setup also takes time.
2. Initial setup also takes time.
What problems is the product solving and how is that benefiting you?
For me, IBM watsonx.data helps address two main challenges — ensuring data quality and making it easily accessible for AI and analytics. In Responsible AI work, having a trusted, well-governed dataset is critical to avoiding bias and ensuring compliance. The platform’s governance tools make it easier to maintain lineage, manage permissions, and apply consistent policies across multiple data sources.
It also streamlines access to both structured and unstructured data, so instead of spending hours gathering and cleaning data, I can focus on building and testing AI models. Using it as a data warehouse has reduced the time it takes to prepare datasets for machine learning, which speeds up experimentation and shortens project cycles. Overall, it’s given me a more reliable foundation for developing AI systems that are transparent, scalable, and ethically sound.
It also streamlines access to both structured and unstructured data, so instead of spending hours gathering and cleaning data, I can focus on building and testing AI models. Using it as a data warehouse has reduced the time it takes to prepare datasets for machine learning, which speeds up experimentation and shortens project cycles. Overall, it’s given me a more reliable foundation for developing AI systems that are transparent, scalable, and ethically sound.
IBM Watsonx Usage Experience
What do you like best about the product?
I have Watsonx for IBM Call for code as it is a Pre-requisite of the Competiton to use the IBM Watsonx. IBM Watsonx has a wide range of AI Products which aligns well with the different usecases. It has it's own Foundation Models Like Granite which we used in our IBM Cal for code Project it's integration with the multiple other models is also easy liek for example Hugging Face Repo and DB Connections as well code Deployment in IBM Cloud. One good thing was the have documentation and walkthrough docs/videos for each and every AI model/functionalty Implementation. These docs/videos helped reduce some time in getting started as they are to the point. Talking about the customer support it is very quick i got problem with my account and got resolved in within a day or so. I have used these IBM Watsonx Three times and alway feel the Functionality and the power of AI integerated tools is amazaing.
What do you dislike about the product?
The things that i felt could have been more better is the limited Third party Resources and integrations though it has few popular tools and integration for some use cases the watsonx does not support them. The Pricing is more compared to other open resources example if i need Large Model Training or multi model usage in watsonx AI the cost increases there is no proper tanspaernecy in Cost upfront as comaprted to AWS. If i want to use the Watsonx AI with non IBM Tools custom connectors which by user needs to be build up is required which is time taking and some times the implementation goes waste.
What problems is the product solving and how is that benefiting you?
The AI Models it has huge computatuion and capable of Handeling Large amounts of data sets, example : Granite Models. These Granite Models already pretrianed with large amounts of data and for use case we have used LLM for passing our use case data as context for the Training Models to generate the results for us. The Results are 75-80% accurate. Teh IBM Granite Models have language support where it support large number of Languages across the world. Since it is integrated with the IBM Cloud everything becomes easy from development to Deployment But, if we want get the Third part tools which not supported by IBM is a bit complex to get it working. Rest it is dtraight forward approach if we are using everything like tools, models and apps from the IBM Cloud.
Makes working with data much easier
What do you like best about the product?
I like how easy it is to manage and search large datasets using the platform. The AI-assisted data preparation tools help me clean and organize data much faster than doing it manually. The interface is user-friendly, and the integration with other IBM products makes it easy to fit into our existing workflow. It also handles large amounts of data without slowing down, which is a big plus for my team.
What do you dislike about the product?
Some of the more advanced analytics features have a steep learning curve and require extra training to use effectively. Also, the cost might be on the higher side for smaller companies. Lastly, it needs a stable internet connection for most operations, so offline work is limited.
What problems is the product solving and how is that benefiting you?
IBM watsonx.data helps us centralize and manage large volumes of data from multiple sources in one platform. It reduces the time needed for data preparation, cleaning, and organization, allowing our team to focus on analysis and decision-making instead of manual processing. The platform’s AI-driven tools improve the accuracy of our datasets, which leads to more reliable insights for our business. Overall, it has increased productivity and made our data operations much smoother.
It's good but not so good, actually the editor is not so good but other than that it is awesome
What do you like best about the product?
The best things about watsonx.data is its UI, the way it is designed I loved it and also ease of accessing every single thing on the platform
What do you dislike about the product?
I can't say i dislike it but it is not upto my expectations from watsonx.data and it is Code editor of this platform, It can be design better and also there should be some flexibility like other code editor.
What problems is the product solving and how is that benefiting you?
I had to learn and practice some technologies like Docker and kubernatics and for that i have to install it in my personal computer but in IBM watsonx.data it is not required we can use it very easily like virtual computer with taking that much space and also works perfectly
Helped Us Cut Down Client Onboarding Time at Citi
What do you like best about the product?
I work as an Assistant Vice President in Citi’s client onboarding team, where we handle large volumes of client data from multiple sources — regulatory checks, KYC documents, transaction history, and internal risk systems. Before using watsonx.data, this information was spread across different tools, which made it slow and sometimes frustrating to pull together for verification. We needed a single platform to bring everything into one place so we could move faster while meeting strict compliance requirements.
Watsonx.data has given us a dependable central platform for storing and querying client data. Queries that previously took minutes now return results much faster, even with complex joins and large datasets. I also value its tight integration with IBM’s governance and security features, which means compliance checks happen in the background without extra manual work. Sharing consistent, up-to-date data across teams has also become much easier.
Watsonx.data has given us a dependable central platform for storing and querying client data. Queries that previously took minutes now return results much faster, even with complex joins and large datasets. I also value its tight integration with IBM’s governance and security features, which means compliance checks happen in the background without extra manual work. Sharing consistent, up-to-date data across teams has also become much easier.
What do you dislike about the product?
The initial setup was the most challenging part. Mapping our existing sources into watsonx.data wasn’t straightforward, and a few integrations needed help from IBM’s support team. The interface works fine but could be more intuitive, especially for new users who don’t have prior experience with enterprise data platforms.
What problems is the product solving and how is that benefiting you?
In Citi’s client onboarding team, where I work as an Assistant Vice President, we deal with huge amounts of data from different sources — regulatory checks, KYC documents, transaction history, and internal risk systems. Before IBM watsonx.data, this information was scattered across multiple tools, which meant a lot of manual effort to bring it together and verify.
Watsonx.data has solved this by giving us a single, governed platform where all of this data can be stored, queried, and shared securely. Now we can run complex queries across large datasets in minutes, and compliance checks are much smoother because the governance features are built in. This has directly helped us cut our client onboarding time from nearly two days to less than a day, which not only improves efficiency for our team but also gives new clients a faster, better experience.
Watsonx.data has solved this by giving us a single, governed platform where all of this data can be stored, queried, and shared securely. Now we can run complex queries across large datasets in minutes, and compliance checks are much smoother because the governance features are built in. This has directly helped us cut our client onboarding time from nearly two days to less than a day, which not only improves efficiency for our team but also gives new clients a faster, better experience.
Very powerful and flexible platform for managing different variety of data.
What do you like best about the product?
Great while dealing with structured, unstructured and semi structured data. Highly scalable and easy to implement big data solutions. For me, the AI capabilities stand out like Gen Ai use cases such as RAG. It also has hybrid and multi-cloud deployment.
What do you dislike about the product?
The cost is quite on the higher side and it highly depends on the IBM ecosystem, outside of it some dependencies fail.
What problems is the product solving and how is that benefiting you?
Easily access all my data through a single entry point for updating daily trackers. Ai architecture and advanced analytics, drill through analytics are also very easy and fast to implement!
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