IBM Watson Studio on Cloud Pak for Data Reviews and Ratings

Use Cases and Deployment Scope

Collaboration is the key aspect in whatever projects we do at our organization. We have people from web development, data science, and ML teams working on projects involving all three domains in a single project. IBM Watson Studio on Cloud Pak for Data is a great asset for the data science team where we work on individual tasks, collaborate with teammates, and share findings and insights. It has all the basic tools required for visualization and modeling the algorithm. The IBM cloud Pak has numerous examples for various use cases.

Likelihood to Recommend

It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.

Use Cases and Deployment Scope

We used IBM Waston for learning and helping other fellow members learn some concepts of machine learning. We learned about IBM Waston through Coursera Specialization and then continue experimenting with IBM Cloud for some time. Whether it is using their services or storing objects in a bucket, it was an amazing experience.

Likelihood to Recommend

IBM Waston Studio is well suited if you wanna use some well-known services without investing much of your time there. There are a lot of services that can be used and experimented with. These services are just a few clicks away. Also, there is a free plan if you want to try before actually using the product.

Use Cases and Deployment Scope

IBM Watson Studio on Cloud Pak for Data helps me bring in multiple data streams in batch and streaming mode and helps me to run ETL processes and then run ML algorithms on top of the processed data. The beauty is I don't need to think about managing resources like CPU, storage, and processing elements and focus all my efforts on the data analytics.

Likelihood to Recommend

Well suited for

<ul><li>Data Storage</li><li>Data Warehousing</li><li>Data Ingestion</li><li>Data Analysis using Python</li></ul>

Less Suited for things like

<ul><li>Streaming Data</li><li>ETL tools area</li><li>AutoML algorithms out of the box</li><li>NoSQL Database support</li></ul>

Use Cases and Deployment Scope

Currently, I am a student and I do not have any idea how many students studying and practicing along with me are using IBM Watson Studio on Cloud Pak for Data. Mostly, this platform might be used by the students under the computer science and information technology department. I use it mostly for my projects by learning to implement several concepts, helping me build and strengthen them.

Likelihood to Recommend

It provides a lot of professional services which are not provided by other platforms

Use Cases and Deployment Scope

The IBM Watson Studio is mainly used for one single department, the data science team. It mainly addresses the devops overhead of heavy jupyter notebooks and provides an integrated interface for people who are not familiar with infra and storage. It also provides a point of integration with other IBM services.

Likelihood to Recommend

IBM Watson studio on Cloud Pak for Data is well suited for medium sized teams. It allows for collaboration between technical and non-technical users. It is less suited for companies who already has large built production ML pipelines, as the cost of migration could be high and the initial overhead of learning the tools still remains

Use Cases and Deployment Scope

Storing data in the form of Worksheets and CSV files so that multiple users can use the data partially irrespective of location.

Running and deploying ML and AI Models. It helps - no need to have local hardware. We are able to achieve all the tasks over the cloud.

Used in different parts of the organization.

Likelihood to Recommend

I am not sure whether can use Watson for Robotic process automation. I like the ease of usage of Watson for ML Models and Image processing. I love the way the Project is associated with Assets. I like the different data connectors.

Use Cases and Deployment Scope

I am into mentoring services, so I teach and assist learners on this technology.

Likelihood to Recommend

Watson is good when you do not have applications and software locally variable on your laptop or PC.

Use Cases and Deployment Scope

We mostly use IBM Watson Studio for its Notebook features for running Python codes. It allows us to work on the code together and generate neat reports.

Likelihood to Recommend

If you are a small company with insufficient funding, it would be better to go with open source resources because they are free and do the same job. If you are a bigger company with enough resources, then IBM Watson Studio could be better in terms of security and accessibility.

Use Cases and Deployment Scope

Used to test prototype applications for clients. Mostly used for creating predictive data models, descriptive models, and basic ETL. There are plans to test new speech-to-text and image-to-text applications for new clients in 2021. Cloud storage is a secondary use since it is the only platform that supports older or legacy databases

Likelihood to Recommend

It is well suited for mechanistic models such as time series and descriptive analysis. There is almost no code necessary when creating these models, as it takes the guesswork out of setting up the parameters. There are also models that we've never before even tried because of its complexities but AutoAI shows that these models are sometimes best for the given problem.

Use Cases and Deployment Scope

This system is currently being used with a few students on a data science degree within the School of Computing at our University. We are using IBM Watson as a means to overcome the hardware limitations we have within the our work setting. IBM Watson provides student with access to high powered machines allowing them to run complex machine learning algorithms without having to worry about hardware negatively effecting the performance of said algorithms. It is also a relatively simple system to use, making it a useful teaching tool which requires minimal support for academics. Students have provided positive feedback regarding the use of this service and we plan to expand our use of Watson Studio throughout our other degree options.

Likelihood to Recommend

IBM Watson Studio is very much suitable for data scientists when running a variety of analytical models using various languages such as R, Python and Scala. If you are planning to use data science driven languages in a cloud setting then IBM Watson Studio is a good option as it combines lots of relevant tools such as Notebooks, RStudio and Spark in a single environment. If you are looking to work in these environments as a group then Watson Studio also works well with the distribution and sharing of workspaces. This service however, isn't always the best solution as it can become costly if you are consistently running a large amount of intensive projects.