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IBM Watson Data Platform

 

Watson Data Platform

The first cloud-native data and analytics tool for Data Scientists in the cognitive age

Watson Data Platform is IBM's first cloud native solution to help data analytics teams find and use the right data for data science, machine learning, and predictive analytics. With big data, comes big responsibility—Watson Data Platform enable enterprises to protect and govern their data in order to comply with regulations, notably General Data Protection Regulation (GDPR).

In 9 months, our broader design team shipped a unified experience for data professionals to leverage the power of analytics and big data to deliver the business solutions they need. Try Watson Data Platform for free.

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My Role

I led the planning and execution of all research efforts on the governance offerings within the platform: Data Dashboard, Business Glossary, Policy Manager, and Classification.

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As a design researcher, I worked closely with Jay, our Offering Manager, to define business and product requirements with users in mind. Within our design team, I worked closely with McKenzie, our UX Designer, to leverage user research to drive design decisions.

I also made it a goal of mine to encourage and guide Visual Designers to dig into the user research so that we would elevate our entire teams' domain knowledge and understanding of our users.

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The Problem

With big data, comes big responsibility. Data governance is one of those things that very few people think about, but can keep certain people up at night. Every company's nightmare is having their name plastered on the front page of the Wall Street Journal because of a data scandal.

The delicate balance that our user, the Chief Data Officer, has with the advent of big data is to secure terabytes and terabytes of enterprise data enough to keep their company name off the front page of the Wall Street Journal, and to also provide access to safe, accurate, and rich data to the data professionals that need it to drive business insights and decisions. 

Our Users

The Chief Data Officer (CDO) is an emerging role that ensures an organization’s data is governed in such a way that it is compliant with industry regulations and accessible to teams across the company to enable data analytics.

They are most often the first of their kind in their organization. 

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Chief Data Officers

I want data governance to become an enabler— not a roadblock.
— Chief Data Officer, Fortune 500 Company

Chief Data Officers are change makers in the data industry. They are often brought into organizations to move the company from the traditional paradigm of a walled castle protecting their data to a controlled sandbox where data is available for analytics.

Their end goal is to enable business analysts, data scientists, and data analysts to generate business recommendations based on safe, trusted, and governed data to help the company make data-driven decisions.

To do this, CDOs need a governance program that includes a defined set of procedures, a plan to execute those procedures, and people who are responsible for putting that plan into action. This is all to ensure that data is used to its full potential and in the hands of the right people.

In addition to the CDO, the Watson Data Platform provides solutions for data professionals working from storage to governance to analysis. These personas are work together to go from the journey of data ingestion to data analysis:

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Our Process

It's been a blast working with my team:

  • Bhavika Shah, Design Lead

  • McKenzie Carlile, UX Designer

  • Jay Limburn, Offering Manager

Broader Design Team:

  • Kacie Eberhart, Visual Designer

  • Joshua Kramer, Visual Designer

  • Amanda Hughes, Visual Designer

  • Noelle Hoffman, Visual Designer

  • Tom Workman, Front End Developer

I worked with Jay to scope the governance offering for cloud (as IBM already had legacy products for on-premise data), which eventually became part of Watson Data Platform. 

I led the generative research that influenced our first set of requirements for the product before Bhavika became our Design Lead and McKenzie was brought on as our UX Designer.

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Because data governance is a highly niche and technical domain, I interviewed and synthesized domain knowledge from Subject Matter Expert interviews in tandem with user interviews.

As a design researcher, it's important to me to fold non-researchers into the research process. Even though we were working in 1.5 week sprints, I folded McKenzie into the research process as much as I could so that we can both make design decisions based on research. He's affinitized large amounts of data with me, attended industry conferences to interview clients, and chimed in during user interviews. 

Once user research is synthesized and shared out to the design team, McKenzie sketches and ideates design concepts. I then recruit users to test the wireframes with and come back to the team with user feedback and recommendations to inform the minimum viable experience or product (MVP).

Examples of Generative Research Synthesis or User Testing Synthesis:

In addition to generative interviews and user testing sessions, I was able to advocate for McKenzie and I to attend the IBM led Chief Data Officer Summit. We were the first ever designers to attend this summit.

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We listened and talked to over 22 CDOs about their hopes, dreams, and fears. With McKenzie and Jay, we were able to show early design concepts of the governance offering to get initial impressions and feedback. We've been invited to the last 3 CDO Summits.


Pain Points


Our Solution

Watson Data Platform enables governance teams to embrace a new data governance perspective by enforcing governance programs and driving insights. With the governance offering, we've designed three key components: Data Dashboard, Business Glossary, and Policy Manager.

By improving data visibility and helping to better enforce data security policies, data professionals can now connect and share data across public and private cloud environments.


Generally Available (GA)

Creating the vision and designing Watson Data Platform began in December 2016. At the time, the product portfolio had about 20+ products that did not work well together and each had their own UI. 

Our broader design team developed 3 experiences and brought the entire data journey into a single, unified experience– Data Science Experience (DSX), Data Refinery, and Data Catalog and Governance. 

By October of 2017, Watson Data Platform went beta, and in December 2017 it became generally available. This was quite a feat to accomplish in 9 months. We faced many challenges and this aggressive delivery timeline meant that Design, Development, and Offering Management had to work in constant communication using agile methods to ship our unified product.

We are always looking for new ways to gain a more holistic view of our clients’ campaign data, and design tailored approaches for each ad and marketing tactic. The Watson Data Platform is helping us do just that by quickly connecting offline and online marketing data.
— Michael Kaushansky, Chief Data Officer at Havas


What’s next?

Now that Watson Data Platform is out on the market, our design team is focused on enhancing our offering with AI capabilities. Head over to Watson Knowledge Catalog to see how Watson can help data professionals find the data that they need and govern their data to enable insights.