Faced a steep learning curve but have streamlined end-to-end machine learning workflows
What is our primary use case?
My main use case for IBM Watson Studio is the end-to-end ML life cycle.
A specific example of a project where I used IBM Watson Studio for the end-to-end machine learning life cycle is that I built a data pipeline that takes a Kafka stream and loads the data into our S3 bucket catalog. Then I built a data pipeline on top of it which parses the catalog and provides structured data for our in-house NER recognition model.
What is most valuable?
The best features IBM Watson Studio offers are that it is good for big and complex organizations, it is multi-cloud, it has an on-prem facility, and it also has strong visual tools.
The strong visual tools have helped my organization, which is currently cloud supported and has an on-prem server as well, as IBM Watson Studio serves as a use case for both of them.
IBM Watson Studio has positively impacted my organization by increasing work efficiency. I have noticed the work efficiency increase as it is an end-to-end ML pipeline in one place.
What needs improvement?
I think IBM Watson Studio can be improved.
I wish learning IBM Watson Studio could be easier and more gradual, as it is a complex task. Also, I think pricing is a bit high.
For how long have I used the solution?
I have been working in my current field for three plus years.
What do I think about the stability of the solution?
IBM Watson Studio is stable in my experience.
How are customer service and support?
I have not had any experience with customer support for IBM Watson Studio as I have not used it.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
We are still using Google AI Studio before IBM Watson Studio, and we have not particularly switched completely to IBM Watson Studio.
We are using Google AI Studio as another option, but I did not evaluate other options before choosing IBM Watson Studio.
What other advice do I have?
I would advise others looking into using IBM Watson Studio to just use the tutorials available to see all the features. I rate this product a 4.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
IBM watson.data is a Reliable Data Integration and Secure Hybrid Cloud Management System.
What do you like best about the product?
IBM watsonx.data is an effective multiple projects data access across Hybrid Cloud and very secure data storage platform management platform and even its workload balancing capability is incredible and very reliable big data integration system.
What do you dislike about the product?
This IBM system is very powerful and very friendly platform with simple implementation and easy to configure the functionalities.
What problems is the product solving and how is that benefiting you?
IBM watsonx.data allows easy data accessibility, secure storage for the various IT projects and very useful data integration tool and the real time data analytics creation through the platform is excellent.
A Unified, Scalable Data Lakehouse
What do you like best about the product?
IBM Watsonx.data makes it easy to manage structured and unstructured data in one place. I really like the open lakehouse architecture - it gives us flexibility to store data in different formats while still enabling fast analytics.
The built in governance, metadata management and seamless integration
with open-source engines like Presto and Spark have significantly improved our query performance.
What do you dislike about the product?
The inititial setup required some learning, especially for configuring connectors and access policies.
Also the pricing can be a bit confusing if you are not familiar with IBM's consumption model
What problems is the product solving and how is that benefiting you?
It helped us centralize our data, eliminate data silos, and dramatically improve query performance.
Reporting has become faster, governance is more consistent, and overall decision-making has improved.
Cost optimization through workload separation has also been a major benefit.
Reliable Tool for Handling Large and Mixed Data
What do you like best about the product?
What I like most about IBM watsonx.data is that it brings different types of data into one place in a clean and organized way. The interface is simple to understand, so it didn’t take me long to get comfortable using it. It also handles larger datasets quite well, which is useful when working on analytics or reporting tasks.
I also appreciate that it comes with helpful features around governance and access control. Setting up permissions is easy, and it feels well integrated with other IBM tools, so I don’t have to jump between platforms. Overall, it makes daily data work smoother.
What do you dislike about the product?
The main thing I don’t like is that the initial setup takes some time, especially for someone not familiar with IBM’s overall environment. A few parts need multiple configuration steps, and I had to go through the documentation several times to understand how certain features worked.
Customer support is helpful, but sometimes the documentation could be clearer, which would reduce the need to contact support in the first place. Once everything is set up, though, the system works steadily without much trouble.
What problems is the product solving and how is that benefiting you?
IBM watsonx.data helps me organize different types of data in one central place, which makes daily data work much easier. Before this, data was spread across different systems and it was time-consuming to manage access and keep everything consistent.
With watsonx.data, I can quickly process large datasets and run analytics without waiting too long. The built-in governance tools also help control who can access what, so data stays secure and well managed. Overall, it saves time, reduces manual work, and makes it easier to use data for reporting and analysis.
Flexible Platform with Powerful Integration and Hybrid Architecture
What do you like best about the product?
I appreciate this platform for its hybrid and open architecture, as well as its support for multiple engines. I also like that it integrates with tools such as IBM Knowledge Catalog.
What do you dislike about the product?
My main issues are the high rates and the complexity involved in learning how to use it.
What problems is the product solving and how is that benefiting you?
I am abel to access my data from one place and it's AI ready as it simplifies finding and organizing the data.
Unified Data Access with Smooth AI Integration
What do you like best about the product?
I enjoy how IBM watsonx.data lets me access all my information from a single spot, regardless of where it's saved across various setups. It handles both organized and unstructured data smoothly, allowing for fast operations and cost savings while enabling me to uncover answers more quickly. I also appreciate its smooth AI integration and strong governance features that keep my data secure and well-managed. Furthermore, it provides a unified environment where I can use SQL, analytics, and AI tools together, simplifying work processes for different teams. The platform's support for federated queries makes analyzing data faster without the need for heavy ETL processes, and its ability to handle complex and messy data alongside clean tables under one roof is highly beneficial.
What do you dislike about the product?
Some aspects of IBM watsonx.data could be improved. Initially, it's challenging to navigate due to a steep learning curve, and the layout can be overwhelming for beginners. Integrating it with certain external applications requires more steps than necessary, which could be streamlined. A cleaner design and smoother setup process would facilitate easier adoption for new users.
What problems is the product solving and how is that benefiting you?
IBM watsonx.data consolidates scattered data, reduces cost with a lakehouse approach, simplifies handling unstructured data, unifies tool usage, and enhances governance. It speeds up insights with federated queries, supporting both structured and unstructured data retrieval efficiently.
All-in-One Convenience with Impressive Storage Efficiency
What do you like best about the product?
Having everything in one place is very convenient, and I also appreciate the storage efficiency it offers. That combination makes the experience great for me.
What do you dislike about the product?
Honestly, I can't think of anything at the moment.
What problems is the product solving and how is that benefiting you?
As I mentioned before, I appreciate being able to access everything in one place, and I also find it to be efficient in terms of storage.
Easily Integrate with Powerful Exploration Features
What do you like best about the product?
I really appreciate the capabilities of IBM watsonx.data in supporting my recent project, particularly for creating a function to change the localhost to an IP address on a local machine. This tools adds to my confidence and allows me to explore and gain deep knowledge on specific topics and points relevant to my coding needs. I find it incredibly valuable for running complex concepts and generating PDFs on a Linux server, which is highly beneficial for my project requirements. The integration simplicity particularly stands out for me, as it's very easy to integrate, especially when using AI agents. It supports creating chatbots or AIAgents seamlessly, which expands my ability to implement AI solutions efficiently.
What do you dislike about the product?
I faced a challenge with the key generator during the initial setup of IBM watsonx.data, which made the setup process difficult.
What problems is the product solving and how is that benefiting you?
I find IBM watsonx.data simplifies my project tasks by transforming localhost to IP addresses and facilitates deep exploration and understanding of complex concepts, especially for generating PDFs and creating AI agents efficiently.
Flexible, High-Performance Platform with Outstanding Value
What do you like best about the product?
This platform is extremely flexible and cost-effective. It combines the adaptability of a data lake with the high performance of a data warehouse. Additionally, it offers built-in support for multiple engines tailored to different workloads.
What do you dislike about the product?
It is still relatively new and lacks the maturity found in platforms like Snowflake and Databricks. The user interface is not very polished and can be slow at times. Additionally, the setup process can occasionally be complex.
What problems is the product solving and how is that benefiting you?
Our data is scattered across multiple systems, both in the cloud and on-premises. We have faced challenges with siloed data in these environments. watsonx.data allows us to query data wherever it resides, eliminating the need to move or duplicate it. Another issue we've encountered is that traditional data warehouses are costly and have limited scalability. watsonx.data has helped us reduce costs, as we only pay for what we use.
Unified Lakehouse with Room for Improvement
What do you like best about the product?
I truly appreciate the unified lakehouse feature of IBM watsonx.data, as it allows me to keep all types of data in a single platform, which significantly simplifies analytics and eliminates the hassle of juggling multiple tools. I love the cost-efficient queries; being able to choose the best engine for the workload helps to reduce compute costs and boosts performance, which is a major asset. The strong governance capability is another aspect I value greatly, as it provides centralized access control and data cataloging. This ensures that data remains secure, compliant, and trusted—qualities crucial for enterprise environments. Additionally, the easy access to data across both cloud and on-premises systems without needing to relocate it is incredibly time-saving and reduces the effort required for data queries. Overall, these features make IBM watsonx.data an invaluable resource for managing and analyzing enterprise data.
What do you dislike about the product?
Setting up IBM watsonx.data can be complex, requiring skilled expertise, which creates a barrier for new users. The user interface has a learning curve and needs refinement to be more user-friendly. While integration works well with IBM tools, it needs improvement for non-IBM ecosystems, particularly in supporting multi-cloud systems, which can slow down adoption for organizations using diverse technological environments.
What problems is the product solving and how is that benefiting you?
I use IBM watsonx.data to manage and analyze enterprise data efficiently in a unified lakehouse, reducing costs and improving performance with cost-efficient queries. Its strong governance and easy access to data enhance security and compliance, streamlining AI application development.
