Data Science Experience
An environment for data scientists to research, create, and collaborate.
About Data Science Experience
IBM Data Science Experience is a cloud-based, social workspace that helps data professionals learn, create, and collaborate across multiple open source tools. As a UX designer on this new product, I was primarily responsible for wireframing end-to-end user flows. The robust prototype I built in Axure was critical in getting design feedback. I also contributed to idea generation, storyboarding, and hi-fi mockups.
Team Role
UX Designer
Project Type
Web Application
Duration
8 Months
The Data Science Process is Fragmented
Data scientists face many obstacles in their workflow. They often use different tools depending on the task and find themselves jumping in and out of several environments. When working on a team, sharing project assets can be frustrating because previous work is either hard to find or created with unfamiliar tools.
—Research Insights—
Frustrations in the Data Science Workflow
Finding Relevant Resources
“You need to read academic papers to understand the data, but finding them is very difficult.”
Working in Multiple Environments
“I have to translate projects from SPSS to R or Python before I even start working with them.”
Collaborating Inefficiently
“You end up asking people where everything is, how it’s organized, and how to interface with it.
IBM Data Science Experience
A platform where data scientists can learn on the job, create analytics using the computing languages they prefer, and collaborate with each other.
Discover the Community
Explore featured notebooks, articles, data sets, and tutorials from the data science community. Grab a sample notebook and start experimenting.
Discover the Community
Explore featured notebooks, articles, data sets, and tutorials from the data science community. Grab a sample notebook and start experimenting.
Access Everything on One Platform
Quickly access the community, projects, notebooks, RStudio, and recently opened files without leaving the platform.
Access Everything on One Platform
Quickly access the community, projects, notebooks, RStudio, and recently opened files without leaving the platform.
Collaborate with Peers to Work Smarter
Projects allow data scientists to collaborate across their organization to transform data into actionable data. By taking advantage of shared data sets, notebooks, and tutorials, data scientists can leverage the work of their peers to accelerate their own progress.
Notebooks
Data Assets
Scheduled Jobs
Bookmarks
Collaborate with Peers to Work Smarter
Projects allow data scientists to collaborate across their organization to transform data into actionable data. By taking advantage of shared data sets, notebooks, and tutorials, data scientists can leverage the work of their peers to accelerate their own progress.
Add Data
Quickly add data to a project or notebook by dragging files into the data panel. Access databases by entering an API key in the connections section.
Add Data
Quickly add data to a project or notebook by dragging files into the data panel. Access databases by entering an API key in the connections section.
Work in Context
Add comments, view file activity and related data, and troubleshoot various problems while working within the context of a notebook.
Work in Context
Add comments, view file activity and related data, and troubleshoot various problems while working within the context of a notebook.
An Excited Audience Waits for What’s Next
Data Science Experience released its beta version at the Spark Summit on June 6, 2016. Below are some highlights of what our audience had to say about the Data Science Experience.
These are big changes for IBM since a year ago. I like the focus on developers, data scientists.
The data science experience demo was impressive. I could have spent a lot more time exploring…great work.
You laid out an ambitious goal and I think you’re achieving it. It’s all about the community.
—Research & Design Process—
What Exactly is Data Science?
My team immersed ourselves into the field conducting over 90 interviews and contextual inquiries with various types of data scientists. They ranged from aspiring students in school to seasoned professionals at large companies. I even led some of our internal user interviews.
Data Scientists are Storytellers
Their goal is to get deep into the data and draw hidden insights to help their business make better decisions. Data scientists must share their findings by telling a compelling story using data. Their process is highly iterative, and involves a heavy amount of research and data exploration. Data scientists often collaborate with business analysts to understand project goals and data engineers to get access to quality data.
Data Scientists are Storytellers
Their goal is to get deep into the data and draw hidden insights to help their business make better decisions. Data scientists must share their findings by telling a compelling story using data. Their process is highly iterative, and involves a heavy amount of research and data exploration. Data scientists often collaborate with business analysts to understand project goals and data engineers to get access to quality data.
Understanding the Data Science Process
Our team learned that there are several types of data scientists with a diverse combination of skillsets. However, their general workflow is very similar. We mapped out their processes and highlighted the disparities between them.
Storyboarding Ideas for Direction and Alignment
The team brainstormed several ideas and narrowed them down to 3 concepts based on impact and feasibility. I helped write and create storyboards that addressed how Data Scientists could research, experiment, and collaborate. Our team presented them to data scientists to determine the direction of our product. The storyboards also helped align product management and development.
Wireframing the Experience
As UX Designer, I was responsible for wireframing several end-to-end flows for the product. Specifically, I led the user experience for the community and resources page. The storyboards I helped draft provided the vision for the wireframes.
