Tag Archives: Big Data News

Role of data science in the healthcare revolution

The healthcare industry is playing a crucial role in fighting COVID-19 Pandemic. This unprecedented crisis has accelerated the implementation of many technological solutions in healthcare that had been long struggling to prove their value. Only those countries that have readily adopted these technological advancements in healthcare are the countries that are doing well in the current pandemic situation. One such technology that has helped the healthcare industry is data science. 

So, how crucial is the role of data science in the healthcare revolution? Here is how data science is shaping the future of the healthcare industry.

Accelerating drug discovery

The process of drug discovery takes years and costs billions before it gets approved. The drug needs to pass through millions of testing procedures over the years until it gets approved. But in most cases, even after investing so much time, money, and effort, the drug may get rejected. But this process can be shortened and made more efficient with the help of data science. Data science and Machine learning algorithms can successfully predict the response and reaction of a certain drug to the body and help the scientists to improve it. Thus, data science in the healthcare sector has proven to be of great help in finding a vaccine for the COVID-19 pandemic. 

Improving diagnostic accuracy and efficiency

Despite having huge amounts of health data at hand, the healthcare industry still suffers from high diagnostic failure rates. Each year, millions of patients are misdiagnosed and are given the wrong treatment. This is where data science comes in. With the help of a deep learning algorithm that can read imaging data such as x-rays, CT scans, etc, data scientists analyze and check the results against an extensive database of clinical reports and studies to deliver more accurate results faster. This is how data science in healthcare helps improve diagnostic accuracy and efficiency.

Optimizing hospital performance

This is another major role of data science in the healthcare industry. Data science combined with predictive analytics is a valuable tool that can help optimize the way in which the hospital or a clinic operates. It can optimize hospital staff scheduling, manage supplies, accounting, and can even build efficient action plans for pandemic outbreaks. Thus, data science helps hospitals make better sense of their data and improves business performance.

Virtual assistance

There can be no better example to explain the role of data science in the healthcare industry than virtual assistance. Data scientists have built digital platforms for patients that give them a personalized experience. These are basically medical applications that identify the patient’s disease by analyzing the data that the patient enters on the application. Based on the symptoms and data, the application will predict the disease, condition of the patient, suggest medication, treatment, and precautions required as per the condition of the patient.

The healthcare industry is swimming in data and data is the new oil. However, in reality, whatever data you have in your hand, it is worth very little if you don’t have highly skilled professionals like data scientists who can derive actionable insights from it. This is why the role of data science in the healthcare industry is crucial. With the world going more digital day by day, the world is in need of data scientists who can study and gain useful information from the trillions of gigabytes of data that are produced each day. This way they could not only help the healthcare industry but also all the other sectors in helping them serve the people better. As a premier business school in India, Praxis offers a 9-month full-time postgraduate program in Data Science. With our vast experience in business education, we offer students both the time to understand the complex theory and practice of data science concepts and the guidance from knowledgeable faculty who are available on campus for mentoring. We also have a well-structured campus placement program that ensures interview opportunities with the most significant companies in the field.

9 Must-Have Skills You Need to Become a Data Scientist

This blog by Mirko Krivanek can can be found here.

Usually I tend to criticize this type of articles, but in this case I agree pretty much agree with BurtchWorks, the author of this article, even though the article is more than 6 months old. Note that BurtchWorks is a recruiting firm that recently posted interesting salary surveys for data scientists.

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Below is the skills list they recommend:

Technical Skills: Analytics

1. Education – Data scientists are highly educated – 88% have at least a Master’s degree and 46% have PhDs – and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist. Their most common fields of study are Mathematics and Statistics (32%), followed by Computer Science (19%) and Engineering (16%).

2. SAS and/or R – In-depth knowledge of at least one of these analytical tools, for data science R is generally preferred.

Technical Skills: Computer Science

3. Python Coding – Python is the most common coding language I typically see required in data science roles, along with Java, Perl, or C/C++.

4. Hadoop Platform – Although this isn’t always a requirement, it is heavily preferred in many cases. Having experience with Hive or Pig is also a strong selling point. Familiarity with cloud tools such as Amazon S3 can also be beneficial.

5. SQL Database/Coding – Even though NoSQL and Hadoop have become a large component of data science, it is still expected that a candidate will be able to write and execute complex queries in SQL.

6. Unstructured data – It is critical that a data scientist be able to work with unstructured data, whether it is from social media, video feeds or audio.

Non-Technical Skills

7. Intellectual curiosity – No doubt you’ve seen this phrase everywhere lately, especially as it relates to data scientists. Frank Lo describes what it means, and talks about other necessary “soft skills” in his guest blog posted a few months ago.

8. Business acumen – To be a data scientist you’ll need a solid understanding of the industry you’re working in, and know what business problems your company is trying to solve. In terms of data science, being able to discern which problems are important to solve for the business is critical, in addition to identifying new ways the business should be leveraging its data.

9. Communication skills – Companies searching for a strong data scientist are looking for someone who can clearly and fluently translate their technical findings to a non-technical team, such as the Marketing or Sales departments. A data scientist must enable the business to make decisions by arming them with quantified insights, in addition to understanding the needs of their non-technical colleagues in order to wrangle the data appropriately. Check out our recent flash survey for more information on communication skills for quantitative professionals.

Doing a quick search for becoming a data scientist will provide tons of additional valuable information.