51 IBM watsonx.data Reviews
IBM WatsonX.data is known for its high capability to handle the integration of various data sources and delivering advanced AI powered analytics capabilities. It offers an easy to use UI that will help users to effectively work with, process and analyze big datasets. WatsonX.data shows remarkable scalability and versatility managing both structured and unstructured data formats. In addition, the platform’s machine learning and AI functionalities make it easy to extract actionable intelligence hereby placing it on the top of the list for businesses that want to benefit from data analytics at scale. Review collected by and hosted on G2.com.
I think that IBM Watson X. data is intimidating for beginners, or for people who do not have experience in the advanced AI and data analytics. Getting up to speed with IBM WatsonX.data and working with large sets of data is challenging for the newcomers. On the other hand, though powerful, the platform might be intimidating to novice users because of the sweeping array of options, meaning that it is not a simple solution for people. Moreover, high system demands may make it unsuitable for organizations with little IT resources at their disposal or smaller teams. Review collected by and hosted on G2.com.
Seamless Integration: Watsonx.data integrated smoothly with our existing hybrid cloud setup and data lakes, eliminating the need for costly migrations. It effortlessly pulled data from SQL databases, CRM platforms, and even legacy systems.
AI-Powered Insights: The built-in automation for data governance saved us countless hours. For example, identifying anomalies in real-time transaction data became 40% faster, improving our fraud detection accuracy.
Scalability: Handling terabytes of customer behavior data during peak sales periods was seamless. We scaled resources without downtime, which was a game-changer for quarterly reporting.
Hybrid Flexibility: The ability to deploy on-premises and cloud environments gave us control over sensitive data while leveraging cloud elasticity for analytics workloads. Review collected by and hosted on G2.com.
Learning Curve: Initial setup required deep dives into documentation, and some team members found the interface non-intuitive. However, IBM’s customer support provided helpful tutorials.
Cost Considerations: While powerful, the pricing model may be prohibitive for smaller teams. We’d love more flexible tiers for mid-sized projects. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
User friendly, easy click and connect features, End to end data services.
i like the data security with governance, keep the lilits of the data. I frequently use this for my easy data integration and processing Review collected by and hosted on G2.com.
cosstly to use with heavy resources, ifeel i should incorporate more anytical parts and streamlining of data Review collected by and hosted on G2.com.
It has inbuilt data lakes, tools for security purposes. It has everything combined in one place that saves time and efforts. Review collected by and hosted on G2.com.
It doesnt support with the other ecosystems like AWS. It has deep learning curve Review collected by and hosted on G2.com.
IBM Watsonx is an open source tool that contains safe features and by which I have successfully integrated it with my company's data process system. The intention was to create a secure AI based process system that the company could rely upon. The reason we set up IBM Watsonx as part of our new AI projects at first is for the good data science that comes along. For this cause, Watsonx is one of the most scalable tools. Review collected by and hosted on G2.com.
Even though IBM watsonx.data is very scalable, it is also very costly and resource heavy and the cost can drastically increase as you try to analyze large amount of data and you may even notice slight lag too. Review collected by and hosted on G2.com.
It's perfect and unique which helps all the stakeholders in the future. Review collected by and hosted on G2.com.
1. Complexity: Setting up and configuring the platform may be challenging for users without prior experience or technical knowledge in big data environments.
2. Pricing: For small or medium-sized enterprises, the cost associated with Watsonx.data could be considered high compared to other cloud-based data platforms.
3. Integration challenges: Although Watsonx.data supports multiple data sources, integrating with certain legacy systems or less common third-party tools might require additional effort.
4. Learning curve: For users new to IBM's ecosystem, mastering the various features and functionalities of Watsonx.data could take time. Review collected by and hosted on G2.com.
IBM Watsonx.data is the best choice for the safe use and best-featured data for your management. Working in a large collection just when needed, starting from scratch up to using the data to get solutions for various data problems, could be helpful in terms of time and effort. With WatsonX.Data, we can quickly train, tweak, and test different machine learning models and then put them to use. The sandstone models are used for fine-tuning tasks that are specific to them, and granite is the base for GPT-like architecture. It saves time, money, friendly to the environment, and is also so much effective. Review collected by and hosted on G2.com.
The APIs integration could be improved and the performance lag should be reduced also. Review collected by and hosted on G2.com.
Best in using loaded data interact with datasets and use accordingly and learn with projects Review collected by and hosted on G2.com.
UI can be more specific and easy to understand the flow Review collected by and hosted on G2.com.
