Data Science Applications
Data science has allowed us to accomplish major goals that were not possible or would have taken a great deal more effort and time just a few years ago.
Data Science for Healthcare
Data science has led to a number of breakthroughs in the healthcare industry. Now, medical professionals have access to a large amount of data through EMRs and clinical databases. They can also use personal fitness trackers. They can better diagnose illnesses, provide preventive care and improve their diagnosis. The sensitive nature of patient information makes data security even more critical in healthcare.
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Data Science for Autonomous Vehicles
The data revolution has also affected the road. Tesla, Ford and Volkswagen develop their autonomous cars using predictive analytics. These cars transmit information by using thousands of tiny cameras and sensors. Machine learning, data analytics and predictive analytics can help self-driving cars adapt to speed limits.
Data Science and Logistics
UPS utilizes data science to maximize efficiency, both internally and for its delivery routes. ORION, UPS’ On Road Integrated Optimization & Navigation Tool, is a data-driven tool that uses algorithms and statistical models to optimize routes based upon traffic and weather. It is estimated that data science saves the logistics firm millions of dollars in fuel and delivered miles each year.
Data Science in Entertainment
Ever wondered how Spotify is able to recommend the perfect song based on your mood? Netflix can predict what you’ll enjoy watching. These streaming media giants use big data to learn your preferences and curate content that they think will appeal to you.
Data Science for Product, Sales and Market Research
Data scientists are relied upon by many businesses to develop time series forecasting models that help with inventory management and supply chain optimization. Data scientists are sometimes asked to provide proactive recommendations based on budget forecasts generated by financial models. Data mining allows you to segment your customers according to their behavior, and then tailor marketing messages for certain groups.
Data Science and Finance
Machine learning and data analytics have saved the financial industry millions of dollars as well as incalculable amounts of time. JP Morgan’s contract intelligence platform extracts and processes vital data from thousands of commercial credit agreements each year. It takes just a few hours to accomplish what would have required hundreds of thousands hours of manual labor. Fintech companies like Stripe and Paypal invest in data science to create machine learning tools that detect fraud and prevent it.
Cybersecurity Data Science
Data science is useful in all industries, but cybersecurity could be the most important. Kaspersky, an international cybersecurity company, uses machine-learning and science to detect hundreds thousand new malware samples each day. Data science is essential to our future safety.
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Data Science: Challenges and Benefits
Data science is not an exception. It has its pros and cons, just like many other tech innovations.
Data Science: Benefits
· This tool helps in business forecasting and decision-making
· Supports complex data analysis
· Cybersecurity protection is improved
· Visualisations and quick business reporting
· Enhances scheduling and recommends service
Data Science: Challenges & Opportunities
* They are just as susceptible to prejudice and discrimination as humans
Security threats are possible due to the amount of data collected
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