IBM Watson Studio

The benefits of IBM watson studio is that it manages the infrastructure for users who are for the most part, not technical. Other open source solutions do exist, however extra devops effort or developer resources are required to build host and maintain such services, and with open source tools the support for bug fixing can be less defined.

Jupyter Notebook or RStudio is a remarkable feature. And we can use R code Comments section Python and many more. Export of the Notebook in many forms like ppt and pdf and html. We can use multiple notebooks. We can integrate even R. We can use SCALA and set the required environment.

Its easy to access, and all your work can be at one place. You do not need multiple tools to be downloaded locally.

If your employees are not as trained in programming and data science, it could be a good alternative to quickly train them [in] the basics.

Some members of staff were upskilling using courses that utilised IBM Watson Studio and they found it to be a particularly useful tool for accessing a large variety of kernels, data sources and compute integration. Having access to a community of 20 million data scientists and the ability to collaborate with colleagues and users easily has had a significantly positive impact on the learning experience for a large portion of our students. More and more researchers and academics are picking up this service as a convenient way to integrate open source stools which are essential to data science.

Coursera introduced us to IBM Watson Studio (formerly IBM Data Science Experience). We never considered using the open-source tools directly because they were already available on the platform.

When analyzing the data of the organization, as a data analyst it is not my objective to learn about how to set up tools and look after infrastructure. The IBM Watson studio stands out where we use tools to help us focus on our main activities. The best part is the easy setup and use [of] the IBM studio.

I used both IBM Watson Studio and Jupyter Notebook as this solved a lot of hardware issues that our users were facing. Some users didn't have the necessary storage requirements to hold all of the data files for our projects or their machines didn't have enough power to execute complex analyses. Using Cloud Storage to host the data and connecting that to the Jupyter Notebook made it possible to have one central repository that our developers could work on - thereby eliminating the hardware issues mentioned above.

Yes I [chose] IBM Watson [Studio (formerly IBM Data Science Experience)] because it offers wide range of features and its more flexible

IBM Watson Studio [(formerly IBM Data Science Experience)] is a one stop shop. Since it can integrate with other open source tools, it makes it easier for me to carry out all my task on one platform.

Actually the reason I chose Watson Studios was it was part of the Coursera Data Science training modules and learning content. Although we did use Jupyter and RStudio as well. I'll definitely use and experiment with the 350 products/services that is available. Currently just practicing coding and doing the basic things with Watson studios.

We are on a journey to evaluate and gain benefits. This will be evaluated and captured as we move along our journey.

We use R Studio in addition to Watson Studio. We typically do POCs in R and then upscale to Watson Studio for production, because the IBM infrastructure means great governance and compliance and a minimum of system administration after deployment. With the new OpenScale ML management, it will also provide more transparency in models.

Ease of use, and ability to allow business analysts to use the tool without special software code training that is required in Jupyter. We are strong advocates of Jupyter advocates.

We got it as part of our package with IBM Integrated Analytics systems. Additionally, since we are predominantly an IBM shop this was an easy decision.

Demonstrated success by airlines have been our primary motivation behind using Watson over others. We are still open to other solutions but Watson seems to have a lot of promise for the travel vertical

We [chose Watson Studio because we] received investment from an ex-IBMer

This platform helps to facilitate the broad user base. For example, it supports everyone from hard-core data scientists, who do in-depth coding, to citizen data scientists; even all the way to business analysts.

One advantage is that Watson Studio uses a lot of open source solutions and brings together numerous popular tools for data science on a single platform. For example, we use a lot of Python and R, and Watson Studio's single platform brings convenience when we're testing different libraries. Other tools are less comprehensive compared to Watson Studio.

We chose Watson Studio because of its robustness, community, and the quality of documentation supporting its offering.

Hong Kong University was teaching non-technical students data science. We've looked at a couple of platforms and found that DSX had a couple of Jupyter NBs to start and it was a minimal effort on the part of Lecturers to produce a lesson plan. However, the erratic nature of Apache Spark in R was a big letdown.

Watson Studio comes with Jupyter Notebooks and RStudio built in! If it did not, we would not be using it. It is the management and integration of these open source tools (including Spark) with other value-added IBM products like Db2 Warehouse on Cloud, and Watson Analytics that is what makes Watson Studio a more interesting proposition than the open source components alone.

In terms of benefit realisation, I think we were definitely able to learn new skills using the environment, but as stated previously, found some of the integrated components e.g. Data Connect and Watson Analytics to be too limited and simplistic for a sophisticated Enterprise customer deployment

Chose it due to being an IBM Gold Partner, and wanted to test the new powerhouse. Additionally, it was said to become more integrated with other serivces, that has come. So far we have realized no benefits from Watson Studio, as it keeps changing. The small benefits we've had are when working in a team, but then we could have saved time due to the changing nature of Dsx over the last 6 months.

Well, it helped very much with the integration with Spark and I'm aware of the utility of Watson services.

Currently we are still evaluating.