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Solving DataOps for Healthcare Analytics

Data Science & 21st Century Healthcare

At John Snow Labs, we believe that data science will be a major driver of progress for 21st century medicine. This view of the future was stated by Khosla and superbly envisioned by the Stanford Biomedical Data Science Initiative:

“A world where your data transforms not just your health, but the health of people everywhere. Where doctors instantly search millions of medical records to find what worked for patients just like you. Where new drugs are developed — and new uses are identified for existing drugs — at rapid speeds. Where we can finally predict diseases in both people and populations and prevent illness before it even occurs. By harnessing the power of large-scale computing and data analysis, we’ll make this world a reality.”

We believe that among the ecosystem of technology companies, healthcare providers, research, government and non-profit organizations working to make this a reality, there is a gap in providing quality Data Operations – finding, cleaning, formatting, updating and publishing data for analysis.

As a symptom, data scientists spend 50%-80% of their time today preparing data for analysis. This is recognized as a key hurdle to insights, which data scientists are not well fit to address. As a result, we believe that “DataOps” will emerge over time as its own discipline.


John Snow Labs is a data operations company. After building real projects & products for over a decade, we realized first-hand that a core issue impacting the productivity & success of data science projects is a lack of realization of how hard the data operations challenge really is.

Andy Palmer’s excellent post – Why it’s time to embrace DataOps as a new discipline – provides background on this emerging field, and draws parallels between DevOps and DataOps. We share the same view, but started our definition with the singular goal of the field – to prepare data for analysis.

Combining our experience and that of many others, we have broken down the multiple problems causing data scientists & analyst to spend so much of their time preparing data into multiple root causes. Then we’ve reimagined what the world would look like once all of these were fully resolved and done right, and redesigned all the processes & tools required to make that happen. This has led us to define DataOps around these six core challenges:

  • Data Engineering
  • Data Quality
  • Data Evolution (Updates)
  • Data Integration (Interoperability)
  • Data Privacy, Security & Compliance
  • Collaboration & Domain Expertise

We deliver solutions that “just work” for these challenges, focusing on the healthcare domain. We serve software and data science companies who are looking to outsource data operations to a trusted specialist. We make them faster by enabling them to focus on what they do best.

Why healthcare?

Our mission is to Accelerate the use of data to improve human well-being.

Leveraging the CDC’s definition of well-being, this covers physical, emotional, psychological, social and economic well-being, as well as development and activity, life satisfaction and engaging work. Multiple studies have associated these factors with positive outcomes for self-perceived health, longevity. healthy behaviours, mental and physical health, social connectedness, productivity, and factors in the physical and social environment.

We are named in honour of John Snow, who was a physician in 19th century London. He is considered one of the fathers of modern epidemiology, in part because of his work in tracing the source of a cholera outbreak in Soho, London, in 1854. His findings inspired fundamental changes in the water and waste systems of London, which led to similar changes in other cities, and a significant improvement in general public health around the world.

Over 600 people died within several weeks during the Soho Cholera outbreak. John Snow identified the source of the epidemic by analysing data – specifically, he built a detailed map of all the households where people died, and subsequently came to the conclusion that the fault was one public water well that all victims had used. The pump was taken out of service and the cholera outbreak ceased. The big insight was that cholera was a waterborne disease – a fact that the academic establishment did not believe at the time. John Snow had to pick a public, data-driven fight to make that case.

Our goal as a company is to support as many John Snows as we can. For him to be successful, a lot of people had to go house by house to collect, check and aggregate the data that he needed to make the insight that saved lives. That’s who we are – working behind the scenes to make today’s healthcare game changers successful. We help them move faster by focusing on what they do best.

Can we help you change the world faster?

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