All Articles by Date

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My Top 10 Predictions for Data Product Leaders in 2022

By Brian T. O'Neill | January 3, 2022

Below are ten 2022 predictions for data product leaders and organizations trying to leverage ML and analytics in their software, tools, apps, and services. From the lens of a consulting product designer. Yea, you head that one right. If that PhD in physics, statistics, math or engineering in you is already making you cringe, you may depart this … Read more

Top 10 Experiencing Data Podcast Episodes for 2021

By Brian T. O'Neill | December 14, 2021

Everybody loves a Top 10 list at the end of the year! How about one with pretty lousy data to back it up? 😉 Analytics on analytics here ladies and gentlemen! Since I know this audience will probably be asking what the data is behind the ranking, it’s pretty simple: it’s the number of downloads … Read more

Data as Product: Links to Talks and Articles on Building Data Products

By Brian T. O'Neill | November 22, 2021

A link list of articles and resources on building data products, and particularly the mind shift involved in approaching data products as just that: products, not projects. Is something missing here? Shoot me an email and let me know. From Data to Product (Newsletter, Eric Weber) Run Your Data Team as a Product Team (YouTube) feat. … Read more

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MVPs: The Slow, Expensive Way to Build Data Products?

By Brian T. O'Neill | July 20, 2021

Is there a faster way than MVPs to create data products that actually get used, are simple, and are trustworthy?

10 challenges internal data leaders will face creating a revenue-generating data product

By Brian T. O'Neill | July 6, 2021

Satisfying internal vs. external customers is not the same. What do data science, analytics, and engineering leaders need to know about the messy world of birthing a new commercial data-driven product?

Why software teams need to look beyond “user-centered” when referring to ML or AI-driven data products

By Brian T. O'Neill | June 24, 2021

As a designer, I used to say “user-centered”-a lot. It’s terminology we now hear from non-designers now, people like many of you. That’s a good thing. But, I want you and your teams to think bigger. For me, that “user-centered” descriptor is missing something about design, and particularly so if you are working on ML/AI systems. … Read more

Heads vs. Hands

By Brian T. O'Neill | March 17, 2021

If you’re struggling to solve human problems with data, the mindset of your analytics org may be the problem.

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Intergalactic data infrastructures != customer value

By Brian T. O'Neill | February 1, 2021

Ok, let’s dive into another reader question. This time from Loris via LinkedIn originally: Cheers, Loris My take? Just buy Snowflake – it will fix everything. Just kidding. Actually, one thing I think I’m hearing more from leaders (which is GREAT) is that it’s not the technology that’s the problem. “The technology part is easy.” … Read more

Collection of tools and hammer on a wooden board.

“No more dashboards!”

By Brian T. O'Neill | January 11, 2021

Is it time to stop using dashboards in analytics solutions and data product design?

Bison blocking a country road. by Yann Allegre

How to get 1 x 1 research access to users of enterprise data products—when your own company is in the way

By Brian T. O'Neill | December 21, 2020

Are you a leader in charge of creating innovative ML and analytics solutions within a very large enterprise organization? Getting the “makers” of the solutions talking to real end-users can be extremely difficult. Here’s how to navigate the gatekeepers and bureaucracy so that the data products you spend so much time and money building actually are useful, usable, and valuable.

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AI / Product Management / UX Design Predictions for 2021

By Brian T. O'Neill | December 17, 2020

I’m not putting out a long list of 2021 predictions, but I have a couple that I will mention to you that are on my radar. First, AI/Data Product Management Seems to be Picking Up There seem to be more jobs appearing in product management in the AI/ML space, in particular. I am not sure why we don’t … Read more

jars of seeds spilling out onto a white surface

Does an analytical mind block your innovation and creativity?

By Brian T. O'Neill | October 13, 2020

Data science, analytics, and engineering are in-demand skills, however, when building customer-facing applications and data-driven products, organizations rely on innovation to unlock the power of this data. How can analytical minds practice creativity that leads to innovative solutions?

Design Audit: Spotify for Artists

What’s Wrong with Spotify’s Analytics Emails (a Design/UI/UX Audit)

By Brian T. O'Neill | October 1, 2020

Today, I’m sharing my impressions of one of Spotify’s analytics touchpoints—a monthly email I receive with a boatload of design choices I mostly hope you will not copy, especially if you’re working in an enterprise capacity. Most of you by now probably know I have another career as a professional musician, and that includes having three recordings I … Read more

Re: Your “Home Depot” Approach to AI/ML

By Brian T. O'Neill | September 25, 2020

Sorry, returns not accepted.

Empty soccer pitch

Better data visualization won’t convince me when to play ⚽️ again

By Brian T. O'Neill | September 14, 2020

Presenting data and evidence isn’t the same thing as providing indispensable decision support, especially when your insights are experienced in a software application with no Powerpoint deck, narrator, or intimate storytelling.

Designing for AI (UX, UI)

By Brian T. O'Neill | August 24, 2020

This is an ongoing list of links to articles, slide decks, toolkits, and other resources around designing AI user experiences.  I will keep this updated. 7 Steps to AI Products – Allie K. Miller (slide deck) UX in the Age of AI: Where Does Design Fit In? – Carol Smith (slide deck) AIMeets.design PDF tool kit (Nadia Piet) … Read more

Inside view of empty airliner by JC Gellidon

(8) reasons why data visualization training for your BI team may not increase analytics adoption

By Brian T. O'Neill | July 21, 2020

Customers want simple, well-designed decision support tools and UX’s that are actionable. Businesses want to see value from data and adoption of data-driven decision making. However, the UX that is afforded to is often simply a byproduct of the analytics team’s engineering, or, at best, “data viz” efforts—and it’s not working. A decade later, success rates for data projects remain unchanged, despite vendor/BI tooling improvements. What are BI/analytics teams still missing? Design.

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Humans – The Weak Link in your ML / AI Strategy?

By Brian T. O'Neill | June 23, 2020

In many cases, machine learning needs to be deployed to augment human decision making, not automate it. What are you doing to account for this dependency on the success of your data product?

My Too-White Data Podcast Looks ~Like This: 🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲👩‍🦰👨🏾

By Brian T. O'Neill | June 12, 2020

Self-reflecting on #BLM, the makeup of my podcast guests to date, racism, and the responsibilities of consultants with platforms and audiences in fighting injustice.

Covid-19 Healthcare Coalition Decision Support Dashboard

A UI Design Audit of MITRE’s Covid-19 Decision Support Dashboard

By Brian T. O'Neill | May 29, 2020

I performed a rapid UI/UX and data visualization audit on the MITRE Covid-19 Healthcare Coalition Decision Support Dashboard. Watch it here, and see my recommended design changes the team should make.