What Is the Data and Information Strategy for Cloud-Based Applications Today? | Go Beyond the Connection Episode 25
At Acupath Laboratories Inc., CIO Thomas Dewar has spent decades proving that strong IT isn’t about chasing new tools—it’s about designing systems that endure. His data and information strategy for cloud-based applications puts people first, ensuring technology remains reliable through any crisis.
Simplicity as a Strategy for Sustainability
Simplicity is the cornerstone of Dewar’s leadership. Early in his career he turned hand-written lab reports into automated dashboards that sparked better decisions. Now he applies that same clarity to enterprise cloud architecture, ensuring teams can understand and maintain systems without dependency on individuals.
“We rebuilt the entire company infrastructure as a web-based application in Azure so that it’s always available and they can use it at any given point in time.”
Validated Data Before Automation
AI is only as trustworthy as its inputs. Dewar requires data validation before automation to ensure repeatable, verifiable results. His teams treat data integrity as a quality-control discipline, not a checkbox. By grounding analytics in a data and information strategy for cloud-based applications, they protect both accuracy and accountability.
Designing for Continuity
From 9/11 to COVID-19, Dewar has learned that continuity depends on decentralization. Cloud redundancy allows Acupath staff to work anywhere without interrupting critical lab operations. That operational flexibility demonstrates how a well-structured data and information strategy for cloud-based applications safeguards uptime and performance.
Leading with Empathy
Empathy guides his technical choices. He observes how employees actually use systems and builds tools that support those behaviors instead of forcing new ones.
“Understanding the business and knowing what it is that the people do is the key thing.”
Takeaways
Episode Highlights
- Why simplicity outlasts complex architecture
- How validated data strengthens AI confidence
- Lessons from crisis-driven infrastructure redesigns
- Empathy as a technical discipline
- Designing systems that survive leadership changes
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