IBM watsonx.data as a Service
IBM SoftwareExternal reviews
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Data as a service, i think this is something fresh and new
What do you like best about the product?
The reason i explored IBM watsonx is, in my current org, we were also building a similiar kind of product, not at this scale but many of the funcitonalitier are common, the feature i liked specially is their prompt lab and how well it is easy to implement, and that actually provides a very good simulation for building different kinds of usecases a person may have. in terms of integration, the data source integration feels seemless a wide variety mainstream connectors are present and easy to integrate, didnt ineracted with the customer support as i didnt have to use it much
What do you dislike about the product?
This not a beginner friendly tool, a person should be well aware of the current AI-scenario, technical terms and how LLMS works upto some level, the UI is clean and minimal but many time i found a bit of difficulty in navigation between different screens, and sometimes i felt everything is given to me, and that made me confused what should i pick, the point is since there is big chunk of business and non-tech professionals are also adopting the use of LLMs into their workflows, and they could be a user of this platfrom, then the platform should hide some of the configuration and handle it via some assumptions, although this is just an opinion i am not very sure of the target audiene of watsonx. for my use i dont see much of use within my team, and current org, there are already many tools which are free and opensource for instance openmetadata, people who want production ready and readiness to scale within their org as they have that much data to take leverage, and exclusive proprietary platform, which is catered for them then this could be a good choice.
What problems is the product solving and how is that benefiting you?
the first is its proprietary nature with ease of integration with my data, that will help organization to quickly bootstrap their products, next is the fine tuning and its simulation with prompt labs, this will actually gives the user an idea how his model will behave without wasting much of his resources on billing and computing,
Review for Open House Leak House
What do you like best about the product?
I'm very impressed about the flexibilty it offers as Apache Iceberg and multiple query engines.
The Way is it being deisgned for handling the AI data for application.
The Feature of Data Governance & Quality Management
The Way is it being deisgned for handling the AI data for application.
The Feature of Data Governance & Quality Management
What do you dislike about the product?
Complicated to Adoption, big learning curve
Integration not that open, seems less capable.
Integration not that open, seems less capable.
What problems is the product solving and how is that benefiting you?
It makes data more meaningful to us & we can use that data for analysis, which further leads to AI Capabilities .
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.
Good AI Platform
What do you like best about the product?
enables highly customizable conversational AI across multiple channels like websites, mobile apps, WhatsApp, and Slack, supporting consistent user experiences .
What do you dislike about the product?
Looks like fre more enhancement can be performed such as on result driven and response.
What problems is the product solving and how is that benefiting you?
transforming over 1 million data points per second into immersive fan experiences via AI-driven content and personalization demonstrating practical enterprise deployment .
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!
Powerful Data Platform with AI Integration
What do you like best about the product?
The most impressive part, however, is how AI and analytics work together, enabling data query and management on both structured and unstructured formats from a single platform. It is also Agile, scale-outable, and interoperable with open data formats like Parquet and Iceberg.
What do you dislike about the product?
IBM watsonx is undoubtedly powerful, but it is not without its drawbacks. For teams inexperienced with IBM’s ecosystem, the setup is multifaceted, the integration is tedious, and the ramp-up phase can be frustrating due to the advanced learning curve. Pricing models are often ambiguous for smaller teams, and along with uneven performance on larger datasets, it becomes increasingly costly. Furthermore, community support is limited and still in the developmental phase, leading to fears around vendor lock-in.
What problems is the product solving and how is that benefiting you?
IBM Watsonx.data addresses critical issues concerning the accessibility, integration, and analytics of data at scale. It helps by consolidating structured and unstructured data across multiple clouds and on-premises systems utilizing an open data lakehouse framework. This allows me to analyze and parse through extensive datasets from various locations without physically relocating them, thus optimizing processes and minimizing expenses associated with storage. It also ensures governance, security, and AI model readiness which supports me by accelerating trusted decision-making while simplifying the operational processes from raw data into insights.
IBM Watson studio best for learning and application for machine learning
What do you like best about the product?
Best in using loaded data interact with datasets and use accordingly and learn with projects
What do you dislike about the product?
UI can be more specific and easy to understand the flow
What problems is the product solving and how is that benefiting you?
Learning project through ciursera
Innovative model
What do you like best about the product?
It has inbuilt data lakes, tools for security purposes. It has everything combined in one place that saves time and efforts.
What do you dislike about the product?
It doesnt support with the other ecosystems like AWS. It has deep learning curve
What problems is the product solving and how is that benefiting you?
Solves the challenge of analyzing the data , storing it and processing it has been made very easy. It's an all in one platform and that's how it benefited me.
IBM watsonx.data: A Scalable Data Powerhouse for Enterprises
What do you like best about the product?
IBM watsonx.data shines with its ability to integrate smoothly into hybrid cloud setups, existing data lakes, and diverse sources like SQL databases or legacy systems-no pricey migrations needed. Built-in AI tools, including real-time anomaly detection and automated governance, speed up analytics and boost fraud detection accuracy. It scales effortlessly for large datasets (structured or unstructured) without lag, ideal for high-volume needs. Users praise its intuitive interface, strong security protocols, and unified data management, which simplifies access and analysis.
What do you dislike about the product?
The platform’s learning curve is steep, especially for non-technical teams or those new to IBM’s ecosystem. Costs can escalate with data growth, and AI features demand hefty infrastructure. Some users report limited customization, slower support, and occasional hiccups integrating niche legacy tools. While robust, its smaller developer community (compared to open-source rivals) might slow peer-driven troubleshooting.
What problems is the product solving and how is that benefiting you?
It pulls scattered data from silos—legacy systems, SQL databases, even cloud apps—into one place, so we’re not stuck fixing broken workflows or paying for messy migrations. The AI tools auto-detect risks (like fraud) and handle governance tasks that used to eat up hours. It also scales smoothly when we’re slammed with data-heavy projects, without crashing or slowing us down.
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