The future looks to data science to handle the ubiquity and increasing complexity of one of our most valuable resources—data. Among the essentials to succeed in the data science space are strong Predictive Analytics and Machine Learning (PAML) tools.
Earlier this month, Forrester published an evaluation of the 13 most notable PAML solutions in order to inform the choices of enterprise leaders. IBM was named a “leader” and Forrester described Watson Studio Cloud as a “perfectly balanced PAML solution for enterprise data science teams.” Needless to say, it has been an exciting month for IBM, as there have also been announcements of new capabilities and updates coming to various members of its data science portfolio.
At a glance, we will be looking at:
- The Future of Multimodal PAML
- Watson Studio as a Leader
- What’s Next from IBM
The Future of Multimodal PAML
PAML solutions have always varied in that some are more code-based while others are more a visual interface. A fair divergence, one might think, in order to accommodate data scientists with different modeling backgrounds and preferences. Like any team, however, a team of data scientists is stronger with collaboration, and as the need for collaboration grows, so too does the importance of multimodal PAML solutions. These solutions provide access to both code-based and visual tools for different members of the team, and they have had an understandable appeal to enterprises for this reason. However, according to Forrester, they will have to do more. In the next two years, enterprise data science teams must support the thousand-model vision, referring to the countless “applications and business processes that could, but do not currently, benefit from predictive models.” Multimodal PAML solutions will have to adequately support the greater needs of the data science life cycle, like model automation and access to open source innovation.
Watson Studio as a Leader
IBM provides a multimodal PAML solution built to survive—and thrive— in this thousand-model future. Watson Studio not only addresses the needs of a team’s data scientists and data science cycle, but it is also, as Forrester noted, “designed for all collaborators—business stakeholders, data engineers, data scientists, and app developers.” As data circulates between stages of the data science cycle, involving different tools and different members of the team, it can be handled entirely within Watson Studio’s multifaceted platform.
A few examples:
- Data scientists have open source coding tools like R, Python, and Jupyter notebooks, along with visual model-building tools like SPSS Modeler, all embedded into a single platform.
- Application developers have model management and deployment tools, with different automation and deployment options, readily available to them.
- Analysts can create visualizations of trends and anomalies in data using interactive dashboards for communication to management and business stakeholders during meetings.
- Project Managers can see what team members are working on for various projects, and which assets are being used for those projects.
Watson Studio’s powerful engineering is complemented by an ergonomic design that makes for intuitive, effective use by all team members.
What’s Next from IBM
There are plenty of exciting updates to look forward to in the future of IBM’s data science offerings, one of which was announced last week at IBM’s signature “Winning with AI” event in New York City. Effective October 2nd, the on-premise offering of Data Science Experience (DSX) Local will be rebranded as “Watson Studio Local.” This rebranding not only more simply unifies all of IBM’s data science offerings under the “IBM Watson” name, but it is part of a greater movement to bring the same great capabilities to customers regardless of whether their platform is local or on the cloud. As part of this, we will see the availability of an integrated SPSS Modeler add-on in the new Watson Studio Local. This tool has been extremely popular for visual-based modeling on the cloud platform, so it will be exciting to see it as an option for the on-premise platform.
We can also expect to see the benefits of Watson Studio’s new partnerships with DefinedCrowd and Figure Eight. As leaders in the data annotation space, these partners have extensive experience with various points in the data science cycle, including data processing and machine learning model training. These partnerships are a part of IBM’s continued collaboration with others in the data science community to make Watson Studio a robust, well-rounded solution.
Already a leader in the industry, IBM is taking no breaks from bringing more powerful capabilities and solutions to its portfolio. If you are interested in learning more about Watson Studio and the benefits that it can bring to your company, please send an email to email@example.com.
Forrester Research Inc. The Forrester Wave™: Multimodal Predictive Analytics and Machine Learning Solutions, Q3 2018 by Mike Gualtieri and Kjell Carlsson, Ph.D., September 5, 2018