Red Dot honors two IBM Cloud Pak for Data services for design excellence

By | 6 minute read | August 5, 2020

Uncork the champagne and toss the confetti: AutoAI with IBM® Watson Studio® and IBM Db2® Warehouse on Cloud — two critical services on our Data and AI platform IBM Cloud Pak® for Data — have received a 2020 Red Dot Design Award, one of the most sought-after international seals of quality in the design industry.

While IBM is no stranger to this prestigious award, we’re especially proud this year because this is the first time we’ve gained recognition for two cloud products simultaneously. Of 6,992 entries, Red Dot honored both AutoAI and IBM Db2 Warehouse on Cloud in its Brand and Communications: Interface Design category. Arin Bhowmick, Vice President and Chief Design Officer of IBM Cloud, Data and AI, noted in a recent blog that winning this dual award “makes the occasion even more special.”

In Q&As with designers, I explored the inventive design thinking behind these two products.

AutoAI with IBM Watson Studio

Designed to help beginners learn data science, AutoAI is a multicloud graphical tool in IBM Watson Studio® that automatically analyzes data and generates candidate model pipelines. Deployable anywhere, the tool solves two key challenges facing most organizations: a shortage of data scientists and the excessive time needed to create a usable and tuned machine learning model. With sophisticated training features and no coding required, AutoAI frees data scientists from mundane tasks to do higher-value work. It also allows app developers and software engineers to become AI experts, equipping them with data science skills and the option to modify codes auto-generated by the tool.

Q&A with Alex Swain, design principal of AutoAI:

How were you able to solve customer pain points using innovative design?

Anything “auto” is usually not trusted by data scientists and was one of the main concerns we had when researching this experience. The design had to convey trust and transparency along with being simple to use. This experience was design-led from the beginning to remove complexities so that anyone could generate AI in under a minute. The UI guides the user to select the data they would like to use and what they would like to predict. The system handles the rest.

What unique features did you use to differentiate the design of AutoAI?

To increase transparency, the team created a custom visualization that displays each step of the AI creation process. This visualization is something no other experience has, and it conveys in real time how AI pipelines are created and helps open the “black box” of AI creation. Users are fully aware of what the system is doing, from data splitting and algorithm selection to hyperparameter optimizations. The design also provides multiple ways to compare and view details of each pipeline to determine the best choice for their needs.

How does good design simplify the lives of our customers?

Good design removes the barriers and frustrations users face by focusing on their needs and providing intuitive solutions that deliver a simplified product experience that they want to use, rather than have to use.

AutoAI Progress map shows the process of data preparation, model selection and hyperparameter optimization.

 

AutoAI Relationship Map describes the relationships among feature transformers, pipelines and top algorithms

 

AutoAI Model Evaluation Measures show cross validation and holdout scores.

IBM Db2 Warehouse on Cloud

Db2 Warehouse on Cloud is a high-performance data warehouse that allows businesses to easily tap into key information without manually sifting through mountains of data. The fully managed, elastic cloud allows businesses to speed time to value by auto scaling and reallocating massive data resources. It also helps ensure that data is securely backed up for disaster recovery.

Q&A with Jessie Pahng, design lead of Db2 Warehouse on Cloud:

How were you able to solve customer pain points using innovative design?

The legacy version of Db2 Warehouse on Cloud was very complex, hard to understand and painful to use. The first thing the design team tackled was to address the core problem—restructuring the information architecture of the console to make it simple and easy to manage. Once we created the sustainable information architecture that mirrored the mental footprint of our end users, we were able to make the overall user experience seamless and intuitive.

What is the “user’s mental model” and how did it impact the design of this product?

Heuristic evaluation of the user’s mental model is an approach rooted in human factor psychology, where we take a deep dive into the needs and goals of target users for a holistic understanding of who they are and what they need to do. We unpacked human cognition to tease out what works, what doesn’t and – most importantly – why. It was crucial to get the full picture so we could streamline the user experience and eliminate pain points.

Tell me more about the design process for Db2 Warehouse on Cloud.

It was a strategic and data-driven design process. We started with a 360-degree analysis, researching users, competitors, industry trends and insights from our DevOps team. We then aligned our goals and objectives with offering managers and engineers to set the vision for the North Star — “ship the product that customers absolutely love.” This guiding principle steered our roadmap and iterations, and we built an experience where users could understand at a glance what’s going on and quickly mitigate issues. However, good design never dies. Part of being innovative means making users happy, so we’ll continue pushing the data-driven process to make sure our design is impactful.

The IBM Db2 Warehouse on Cloud dashboard helps users get a view of all their important data in one glance as well as an analysis of what these metrics mean.

 

Workload management enables users to view how each service class contributes to the whole so that they can manage the overall workload distribution easily.

 

Replication experiences help users save copies of their data and protect their businesses from losing all their information.

About the products

AutoAI with IBM Watson® Studio automatically runs the following tasks to build and evaluate candidate model pipelines:

  • Data pre-processing – Uses algorithms to analyze, clean and prepare your raw data for machine learning, eliminating missing data values
  • Automated Model selection – Ranks candidate algorithms and selects the best match for your data
  • Automated featuring engineering – Transforms your raw data into relevant features that maximize model accuracy
  • Hyperparameter optimization – Refines model pipelines and optimizes evaluations such as model training and scoring, resulting in faster time to value

IBM Db2 Warehouse on Cloud reduces costs by:

  • Scaling storage and compute as needed to supercharge massive, highly concurrent workloads
  • Supporting business continuity and disaster recovery through multiple layers of replication, resiliency and fault tolerance
  • Providing hands-free service with automated database monitoring, uptime checks and infrastructure updates

Next steps

To learn more about AutoAI, available as part of IBM Watson Studio, download this free eBook and try a product tour or start on cloud for free.

To get started with IBM Db2 Warehouse on Cloud, check out these two tutorials and read the solution brief.

Both IBM Watson Studio and IBM Db2 Warehouse on Cloud can be provisioned easily through IBM Cloud Pak for Data as a Service. Sign up for a free trial of a starter set of IBM Cloud Pak for Data services today.

For more information on IBM Cloud Pak for Data, watch our webinar with Forrester analysts and read our newsletter featuring complimentary Gartner Research.

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