Data Science Application, Benefits & Risks

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Data science allows us to achieve major goals which were either not possible, or took a lot more time and effort just a few short years ago.

Data Science Applications

Data science allows us to achieve major goals which were either not possible, or took a lot more time and effort just a few short years ago.


Data Science for Healthcare

The healthcare industry has seen a number breakthroughs thanks to data science. Medical professionals can now access a vast amount of data via EMRs, clinical databases, and personal fitness trackers. This allows them to better understand diseases, practice preventive care, diagnose illnesses faster, and explore new treatments. Data security is even more important in healthcare due to the sensitive nature of patient data. 

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Data Science for Self-Driving Cars

The data science revolution is also affecting the roads. Tesla, Ford and Volkswagen use predictive analytics to develop their autonomous cars. These cars relay information using thousands of tiny sensors and cameras. Self-driving vehicles can adapt to speed limits and avoid dangerous lane shifts using machine learning, data science and predictive analytics.


Data Science and Logistics

UPS uses data science for maximum efficiency both internally and on its delivery routes. ORION, the company's On Road Integrated Optimization and Navigation tool, uses statistical models and algorithms backed by data science to create optimal routes based on traffic and weather conditions. Data science, it is estimated, saves the logistics company millions in fuel and miles delivered each year.


Data Science in Entertainment

Have you ever wondered how Spotify can recommend the perfect song for your mood? Netflix is able to predict what you will enjoy watching. These streaming media giants use data science to learn about your preferences and carefully curate the content they believe will appeal to you.


Data Science for Product, Sales and Market Research

Many businesses depend on data scientists to create time series forecasting model that helps with inventory management and supply-chain optimization. Sometimes data scientists are tasked to make proactive recommendations using budget forecasts based on financial models. Data mining can be used to segment customers based on their behavior and tailor future marketing messages to appeal only to certain groups.


Data Science and Finance

The financial industry has saved millions of dollars and incalculable time by using machine learning and data science. JP Morgan uses its contract intelligence platform to extract and process vital data from thousands commercial credit agreements every year. What would have taken hundreds of thousands of hours manual labor to finish is now completed in just a few short hours. Fintech companies such as Stripe and Paypal also invest in data sciences to create machine-learning tools that detect and prevent fraud.


Cybersecurity Data Science

Data science can be useful in any industry, but cybersecurity may be its most critical application. Kaspersky, a cybersecurity company that operates internationally, uses machine learning and science to detect hundreds of thousand of new malware samples every day. Data science will be essential for our future safety and security.

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Data Science: Benefits and Challenges

Data science is no different. Like many tech innovations, it has pros and cons.


Data Science: Benefits

It helps with business predictions and decisions

* Supports data analysis even for complex datasets

* Improves cybersecurity protection

* Quick business reporting and visualisations

* Improves scheduling and recommends services


Data Science: Challenges and Opportunities

* They are susceptible to bias and discrimination just like humans

The amount of data collected makes it vulnerable to security threats

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