Data and Healthcare

The reason why health care is one of the prime clients of Data Science is that it has been generating massive amounts of data for ages, and now is the time to really push this data to the limits which haven’t been unlocked yet. From precision medication to advanced wearable devices to modern methods of drug discovery, Data Science is changing the way we know healthcare today. Following are some factors how data science is creating wonders in the Healthcare industry:

1. Developing New Drugs: Medicines are why people go to hospitals, and you’ll be surprised to know that every single medicine, which you see in a store has been developed by continuous research of many years and huge investments. And unfortunately, many of the newly discovered drugs prove to be a failure.

   With the help of Data Science, Laboratories can now reduce the time and energy required for developing new drugs. We can combine the case studies, treatment records, tests results etc and utilize machine learning algorithms to create simulations which would tell us in advance whether a drug is going to work on the human body. Not only this, but we are also able to predict how the genes in our body are going to be affected by the drug. This is not only going to increase the speed of research, but also reduce the wastage of money.

2. Advanced Wearable devices: Wearable devices are now all set to become our new health-guards. They can give us time to time update of our and our family members’ health status and record the data for further reference. Moreover, they can detect even the slightest disorder in the working of our body system and inform us immediately. They can detect the diseases even before the symptoms have surfaced.
3. Diagnosis: It’s a sad truth that even after the development of modern technologies, thousands of inaccurate diagnoses occur every year. There is sufficient data to prevent these mistakes, but the traditional techniques are not able to exploit the data.

   With the help of Data Science, we can now carry out extensive medical tests and analyze large amount of data make accurate diagnoses in almost no time. This is also helping the doctors in detecting chronic diseases in very early stages.

4. Precision Medicines: If we look at the traditional methods of Medical Science, we’ll find that there are various sets of problems and particular tests and medicines have been assigned to them. This way, one particular test or medicine is prescribed in all the related diseases. With Data Science, now it is possible to understand the exact problem and devising medicines and doses accordingly.
5. Developing Cures for Incurable Diseases: A large amount of money and energy is being invested in developing cures for inaccurate disease all over the world. Data Science is helping them come together and share each other’s studies, and this is ultimately going to increase the speed of researches. The time’s not far when we’ll have a cure for every single disease on the planet.

Data science is a present-day technology world using a very common term. It is a multi-disciplinary entity that deals with data in a structured and unstructured manner. It uses scientific methods and mathematics to process data and to extract knowledge from it. It works on the same concept as Big Data and Data Mining. It requires powerful hardware along with an efficient algorithm and software programming to solve the data problems or to process the data for obtaining valuable knowledge from it.

The present information trends are providing us 80% of data in unstructured mannered while rest 20% structured in format for quick analyzing. The unstructured or semi-structured details require processing in order to make it useful for the present-day entrepreneur environment. Generally, this information or details are generated from the wide varieties of sources such as text files, financial logs, instruments and sensors and multimedia forms. Drawing meaningful and valuable insights from this information require advanced algorithms and tools. This Science is proposing a value proposition for this purpose and this is making it a valuable science for the present-day technological world.

How Data Science Drawing Insights from Data?

1. For example, present-day online sites are maintaining the huge volume of the details or information pertaining to their customer base. Now, the online store wants to propose product recommendations for each customer based on their past activity. The store got the entire information of the customers like past purchase history, products browsing the history, income, age and some more. Here, the science can be a great help by coming up with train models using the existing details and store could be able to recommend precise products to the customer base at the regular intervals. Processing information for this purpose is a complex activity, but the science can do wonders for this purpose.

2. Let us look into another technological breakthrough where this science can be a great help. The self-driving car is the best instance here. Live details or information from sensors, radars, lasers and cameras generally create the map of surroundings for self-driving cars. The car uses this information to decide where to be fast and where to be slow and when to overtake other vehicles. Data science uses advanced machine learning algorithm for this purpose. This is another best instance to convey more about the science how it helps in decision-making using available details or information.

3. Weather forecasting is another area where this science plays a vital role. Here, this science used for predictive analysis. Details or information or facts or figures collected from radars, ships, satellites, and aircraft used to analyze and build models for weather forecasting. The developed models using science help forecast weather and to predict accurately the occurrences of the natural calamities too. Without science, the data collected will be totally in vain.

Life Cycle of Data Science

• Capturing: The Science starts with the data acquisition, data entry, data extraction and signal reception.

• Processing: This science process the acquired data effectively using data mining, data clustering & classification, data modelling and data summary.

• Maintaining: The Science maintains the processed data using data warehousing, data cleansing, data staging, and data architecture.

• Communicating: This science communicates or serves data using data reporting, data visualization, business intelligence and decision-making models.

• Analyzing: This Science analyzes data using exploratory or confirmatory process, predictive analysis, regression, text mining and qualitative analysis.

“Data is the new gold mine!” The statement holds huge significance when it comes to today’s business world. The current corporate arena is largely operated based on data-driven decisions. You might be surprised to know that each day, about 2.5 quintillion bytes of data is being generated. That’s certainly a massive amount, isn’t it! Now just think what would happen if owing to some system malfunction or any other issue, all this data gets lost. It would be a huge mess for businesses and would cost them a lot. This is the key reason why there is a substantial demand for Data Scientists in the job market. In fact, the job profile of a ‘data scientist’ is already declared to be the most sought after profession in the 21st century. It’s hence the right time for you to ride the growth and build a career that you will be proud of.

Wide Acceptance of Data Science

With Big Data being implemented in almost all spheres of our lives and in the near future, there wouldn’t be any business organization that can afford to ignore the importance of data science. If they do, chances are high that they would lose out on their competition. Smaller companies with adequate data handling skills will triumph over larger corporations with limited data knowledge and experience. Even the start-ups are not losing any opportunity of making data-based decisions. The business world has very well understood the relevance of data science in the modern scenario. If this enormous pool of data can be examined and calculated using a scientific approach, it can help the organizations derive to meaningful conclusions, which directly means better business decisions, more profits, higher ROI.

More Data, More Jobs, More Salary

Be it start-ups or giant corporations, no company exists in the modern age that doesn’t rely on data and analytics for taking business decisions. As per the reports published by McKinsey Global Institute, about 40 zettabytes of data would cover up the internet by the year 2020. This will facilitate a sharp rise in demand for Big Data and Data Science professionals. With more time, the popularity of Big Data shall reach a new level as more companies would start adopting this lucrative opportunity for business growth. With the high demand of qualified professionals and lower supply of the same, as per the economic principles, the salary structure would be quite attractive. It is a given fact that the data scientists are the ones who get higher paying jobs as compared to other engineers and people working on similar job profiles.

Besides, when we are talking about data, how can we miss the opportunity to show some data related to the profession of a Data Scientist? According to a report published by an online education portal, there has been a dramatic rise noticed in the listing and application for jobs related to Data Science. There is a whopping 200% year on year increase in search for ‘Data Science’ jobs, while at least 50% year on year rise has been noticed in the listing of such job requirements. It is hence, evident that Data Science is here not only to stay and survive but to thrive and rule.

Higher Salary Potential

Data Analytics skills are the demand of the hour. Almost every industry is in dire need of skilled professionals who have adequate knowledge to manage the data properly and conclude to meaningful results that will enable businesses to take their operations to an entirely new level. Having said that, it is pretty clear that only trained professionals can gain maximum exposure in this data-driven era and enjoy greater salary structure.

According to a research report published by an international organization, the average annual salary of data scientists globally in the year 2015 was $130,000. Now, the demand has grown even higher, and the salary structure has also increased to a greater extent. In India, the average salary structure for Data Science professionals is quite lucrative. An Analytics professional in India can take in as much as INR 15 lakh per annum in the initial years which goes further higher with experience. The most interesting factor is that Data Science is not only popular in India, but other foreign markets are also seeking highly trained professionals. Hence, if you have the talent and relevant knowledge and are ambitious enough to grow and succeed, Data Science offers you the perfect opportunity to realize your dreams.

At TimesPro, we have partnered with industry experts like Google, Intel, Flipkart, and Fractal Analytics to create a results-driven, comprehensive professional learning program on Data Science, encompassing the core concepts of Data Science, Machine Learning, and Artificial Intelligence. At TimesPro, a Top-Ranked Data Science Institute in Bangalore, we promote a learning environment where students are not only introduced to the essentials of Data Science but are rather prepared to step into the industry with immense confidence and amplified potential. We believe that it is the constant practice that makes an individual adept at his/her job role. That’s why, at our campus, we ensure that our students have enough industry exposure and have in-depth insights into the deep-seated challenges, as well as their solutions. The future world is about to be extremely dependent on how we use data. Hence, our aim at TimesPro is to create industry-ready professionals who can utilize the mounting opportunity and rise with the growth of the industry.