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The identity shift from data consultant to business solutions architect — and why AI is forcing every data professional to make this transition now March has been a month of deep reflection at Steinert Analytics. The type of consulting engagements I envisioned for myself are finally fruiting — but AI is reshaping the game faster than I anticipated. I’ve been having some of the most honest conversations of my career with mentors, clients and fellow data professionals about wha

What a 7-month sales cycle, a flat startup culture, and a healthtech AI client taught me about trust, patience and closing deals that actually compound. February has been the most electric month in Steinert Analytics history. We closed and kicked off a brand new healthtech AI startup client — and from the first call, I knew this engagement was built different. Not because of the scope. Not because of the contract size. Because of what 7 months of relentless sales pipeline wor

How to turn a CFO’s data quality brain dump into one clear KPI and one actionable project Last week, I did an intense data discovery session with a CFO that’s been dealing with data quality issues. Truth be told, this company is not ready for a data transformation (check out my article from December  on knowing if a company is ready for a data warehouse or not). Core sales processes are working, but manually tie back to Google Sheets. The workflows set up in their accounting

I was building data products for everyone except the people who mattered most—here's how I course-corrected I’m stoked to be back writing in the new year. 2026 is off to an incredible start and it gives me chills to think about the progress we’ve made in the last year at Steinert Analytics. We’ve dropped two episodes of The Healthcare Growth Cycle Podcast  in the month of January. They’ve been well received. On the business development front, the first two weeks of 2026 kicke

Real experiences delivering exceptional value as a data consultant—no fluff A few months ago, I wrote about a broken pipeline that cost my client days of downtime. Their financial reporting system broke, and I was directly responsible. I enhanced the client’s trust through 100% transparency and took action on a fix. The low-code data pipeline solutions we use with this client are buggy (to say the least). Truthfully, there’s no foolproof way to guarantee these pipelines run 1

The readiness checklist that separates strategic investments from expensive mistakes Data consulting leads to interesting experiences. Those often involve a range of companies with large variations in tech and data maturity. If there’s one thing I’m learning, it’s knowing how to spot if a company even needs your services in the first place. At Steinert Analytics, we specialize in building data infrastructure and governance programs for mid-market and scale-up healthcare orgs

Why your brownfield data migration is probably doomed (and how to fix it before writing a single line of code) One month. That’s how long a single report migration dragged on because we dove straight into development without asking the right questions first. And it was completely avoidable. I realize this newsletter needs to provide value to healthcare data leaders in the mid-market and scale-ups. As a consultant, I often share perspectives from client projects—the wins and t

20 years of centralized governance beats the data mesh hype every time Imagine you’re the first data engineer who starts at a mid-sized healthcare organization. You’re tasked with modernizing their data infrastructure from brownfield by migrating from on prem into the cloud. In your first week, you get a lay of the land and realize there are 50 legacy Power BI reports directly connected to the database. The database contains source data mainly from their EHR. There are a few

Walking the walk when speed beats perfection—and what I learned selling $100K ROI guarantees under impossible timelines Like the Back to the Future DeLorean’s License Plate, We’re OUTATIME. In this issue, I’m focusing on how to truly walk the walk as a consultant. I think this piece is therapeutic for my own psyche, and selfishly, why I’m diving into it on this week’s Rooftop Insights issue. It’s easy to talk about best practices in data. After 4 years of establishing my bran

Why most healthcare companies need data management, not another AI tool Everyone’s talking about AI agents and LLMs while most healthcare companies are still copying numbers from seven different places into Excel and calling it “the source of truth.” This piece comes from the heart. It sits deep in my bones because it’s ultimately our offer at Steinert Analytics. Since October, tech events have been a heavy focus for me. I’ve written about this in previous issues (specificall

What happens when you admit your architectural mistakes instead of blaming the vendor Three days. That’s how long our healthcare client watched their revenue cycle reporting go stale while I scrambled to fix broken pipelines. And it was entirely my fault. Welcome back to Rooftop Insights! This week, I’m sharing a hard-earned lesson about transparency, accountability, and what it really means to be a trusted data consultant—especially when everything falls apart. The Foundatio

Part 2 of 2: The Data Leader’s Guide to Proving ROI Last week, I promised you Part 2 would dive into revenue growth ROI calculations—going beyond time savings to show you how to quantify the bigger financial impact of data initiatives. After wrapping up Part 1, I went back to our client projects to pull examples of revenue generation ROI. And you know what? This boils too many oceans to write about in a concise and easy to follow way. This isn’t a result of poor implementatio

Why intimate gatherings beat massive trade shows, the power of bringing your tribe, and what Steve Wozniak taught me about staying true to your "why" A Quick Note on Last Week’s Promise: Last week, I promised we’d dive into Part 2 of our ROI series—building the complete business case and calculating total value creation. However, between Kickstart Ohio and other conferences this week, I didn’t carve out writing time until Sunday afternoon. Rather than rush through something a

How to Turn "We Need Better Analytics" Into Hard Dollar Savings Executives Can't Ignore Setting the Foundation When beginning a data initiative, what is the objective of your company/client? Where are they in the data maturity lifecycle? What was the initial pain that brought you on board to help? How is data being used/going to be used as a growth driver for the company? What is a solution that speaks to a significant problem that ties directly to the company’s value chain?

The hidden metadata refresh delay that cost us hours of troubleshooting—and how one API call solved everything The 8 AM Mystery: A Data...

I quit my Fortune 200 job to blast Young Dolph and build a six-figure agency. Here's what happened next I’ve almost run my agency into...

A healthcare data consultant’s Friday morning crisis—and the lesson that changed how I think about professional relationships The...

From SQL to Boardroom: A Field Guide to Thriving in Data's Multi-Hat Reality This past week was a learning journey. 'Tis the season of...

Data Catalogue Series #2: How Information Flows to Recommend Profitable Design We are sticking with a cost effective sentiment from last...

Data Catalogue Series # 1: The foundation that prevents data disasters Last week, I highlighted the importance of documentation on one of...