Learn more about Imran Qureshi

Author Bio

Imran Qureshi

Imran Qureshi is the Chief Software Development Officer at Health Catalyst where he is responsible for all software development in the company. He also leads the Engineering team building the Data Operating System (DOS). Before Health Catalyst, Imran was the Chief Technology Officer at Acupera where he led the team that built the care management platform that was successfully implemented in Ascension, Montefiore, Kaiser, and other health systems. Prior to that, Imran was VP of Engineering at CareAnyware, where he led development of the largest cloud-based EHR for Home Health and Hospice. He spent 12 years at Microsoft, including building the slideshow for PowerPoint and building the email experience for Hotmail. Imran holds several patents and has a Computer Science degree from Stanford University.

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Imran Qureshi

How to Turn Data Analysts into Data Scientists

Healthcare data scientists are in high demand. This shortage limits the ability of healthcare organizations to leverage the power of artificial intelligence (AI). Health systems must better utilize their data analysts, and, where possible, turn some data analysts into data scientists.
This report covers the following:

Healthcare use cases and which ones data analysts can take the lead on.
Specific steps for turning data analysts into data scientists.
How to identify the best candidates among your data analysts.
Recommended resources to get started on an AI journey.

Imran Qureshi

Healthcare Analytics Platform: DOS Delivers the 7 Essential Components

The Data Operating System (DOS™) is a vast data and analytics ecosystem whose laser focus is to rapidly and efficiently improve outcomes across every healthcare domain. DOS is a cornerstone in the foundation for building the future of healthcare analytics. This white paper from Imran Qureshi details the seven capabilities of DOS that combine to unlock data for healthcare improvement:


These seven components will reveal how DOS is a data-first system that can extract value from healthcare data and allow leadership and analytics teams to fully develop the insights necessary for health system transformation.

Imran Qureshi

What Is a Healthcare Data Lake and Why Do You Need One? Imagine a Supermarket

Using a supermarket analogy, this article helps healthcare leaders understand what data lakes are (open reservoirs for vast amounts of data), why they’re essential (they reduce the time and resources required to map data), and how they integrate with three common analytic architectures:

Early-Binding Data Warehouse
Late-Binding Data Warehouse
Map-Reduce Hadoop System

Data lakes are useful parts of all three platforms, but deciding which platform to integrate a data lake with depends heavily on a health system’s resources and infrastructure.
Once understood and appropriately integrated with the optimal analytics platform, data lakes save health systems time, money, and resources by adding structure to data only as use cases arise.