From Gynaecology to Data Science: The journey of Dr Nitin Paranjape

Even experts in this field spend close to 80 percent of their time cleaning up data, which is an absolute waste of humanity.
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Dr Nitin Paranjape started his career as an obstetrician/gynaecologist before venturing into the world of data and business analytics. Nitin, aka ‘Doc’, found his calling in creating intelligent software for Pathology labs and diagnostic centres; the rest is history. Today, Doc is a published author, a revered orator and trainer, and a Microsoft office MVP for the past 17 years. 

In an exclusive interview with Analytics India Magazine, Nitin spoke about his transformational journey from medicine to data and business intelligence


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AIM: What made you switch from medicine to data and Business Intelligence?

Nitin Paranjape: I learnt programming as a hobby while I was studying for my medical post-graduation in 1996. During that time, personal computers were very hard to come by and involved a lot of investment. I started with the Sinclair Spectrum 64kb computer, a gaming console. I got curious about the code behind these games. That’s when I delved into the programming part of it. Later, I developed a program that gave instant access to a patient’s medical history, including prescriptions and their effectiveness. As a result, the queue in front of my office started moving faster. This was a direct value-add which involved no funding, just a database with search. After that, I wrote a lot of medical software for patient management, and it soon became a profession. I also developed the first software to centralise birth and death registration across India. 

AIM: What were the challenges you faced in this transition?

Nitin Paranjape: The biggest challenge was awareness. Data science was quite a new and unexplored field back then. So to explain the concept of data science, I first had to teach the basics of computers.

Another challenge was the cost. Investing heavily in something that did not directly add value to the business was a difficult sales pitch. At the time, bulky hardware and primitive software were the real bottlenecks. The term “IT” did not even exist then. Everything was a struggle. Documentation and books were not easily available, and you had to learn by trial and error.

Above all, customers were reluctant to invest in hardware and then pay for software.

AIM: What’s your advice for a budding data scientist?

Nitin Paranjape: User focus is important. Everyone in the IT industry must acknowledge that your salary comes from business people doing their work and turning a profit. That focus should reflect in every activity you perform. Business value delivery has to be the benchmark. Aspirants should understand the value of data and not just spend their time making beautiful reports with lots of irrelevant data.

Breadth first, depth later. In most fields, depth matters. But in the case of IT, there are too many topics to master. You cannot be great at all of them. But that does not mean you should be ignorant of everything except your area of expertise. You must know something of everything, and in parallel, try to be an expert in one or two areas. Data science is all about retrieving information and putting it forward in the best possible way, and it helps to have more than a few skills up your sleeve.

As a technologist, you must learn all available features and choose the right combination to solve specific business problems. 

AIM: Tell us about a project/challenge that stands out in your career.

Nitin Paranjape: I truly understand what a doctor faces every day and can develop projects that can improve the process. I created a comprehensive clinic management software in 1996 when most doctors were averse to new technology. I developed an extremely flexible software in DOS FoxPro. You could manage multiple specialities using the software. It even had a hardware lock to prevent piracy. The doctor could create patient forms. 

The UI, Data tables, relationships, validations and analytics would be done automatically. However, this was during an era when basic skills such as typing were not everyone’s cup of tea. So then, I created a typewriter where data could be added. So if I’m a dermatologist, my vocabulary would be different. If I’m an anthropologist, my work is different. So I created separate databases for dumping data, but then that data also mattered. And people, at some point, purchased my vocabulary for a particular field. And that’s the real value of data.

AIM: How important are certifications in this field?

Nitin Paranjape: There are multiple angles that I’d like to address here:

1) Recruiter’s point of view: If you’re applying somewhere, the interviewer or the person screening your resume may not have time to judge you or your breadth of knowledge. So, certification does give you that shortcut. Therefore, certifications are necessary to show that you are qualified.

2) Updation: One of the biggest benefits of certifications is it helps you stay updated on the latest technologies and software. 

3) Holistic approach: The content creators for certification courses must look at the topic or subject from all angles to build the syllabus. Certifications help users expand their horizon of knowledge beyond simply what they need to get the job done. For example, if you are learning a programming language, you must at least read the syntax of each keyword, function, parameter, property, method and so on. This is your toolbox. Only after this can you choose the right tools for the right purpose efficiently.

That said, certifications are just the starting point or an eligibility criterion. No certification will make you a complete expert in the field. Expertise comes by going into the finer details, understanding beyond the topic in-depth, what is available, and making sense of all of this knowledge to the best of your ability. That is what one should strive for.

In the long run, your work should speak for itself.

AIM: What’s your long-term vision?

Nitin Paranjape: My vision for the future is two-fold: I want every user to have the ability to :

  1. Spend minimal time in data clean-up
  2. Analyse the data fully and make the most of it

Even experts in this field spend nearly 80 percent of their time cleaning up data, which is an absolute waste of humanity. There are four methods of cleaning data: Manual, algorithm-based, prompt/macro-based and a combination of the three. This approach to cleaning data is absolute stupidity. There are applications like Power Query. Many people in business intelligence use this tool, but not many know of its flexible nature or that it can even be used on an Excel spreadsheet.

More Great AIM Stories

Kartik Wali
A writer by passion, Kartik strives to get a deep understanding of AI, Data analytics and its implementation on all walks of life. As a Senior Technology Journalist, Kartik looks forward to writing about the latest technological trends that transform the way of life!

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